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Dept	#	Course Name [Hide course descriptions]	Credits
E35 - ESE	100	Independent Study	0

E35 - ESE	102	Introduction To Electrical And Computer Engineering	3
		A comprehensive introduction to the theory and practice of electrical and computer engineering. An application area such as multimedia communication systems is used as a theme throughout to motivate the diverse elements of the course. Many fundamental aspects of engineering are covered, including physics and physical devices, mathematical modeling, analytical problem-solving, engineering design, and laboratory experimentation. Course topics and skills are integrated in design projects covering contemporary applications of interest to the instructor and student. Prereq: Phys 117A, and Math131 or 141. Coreq: CSE 131 or 126, plus MATLAB programming. Open only to freshmen and sophomores. Juniors and seniors who are planning to take this course are directed to E35-ESE-233 Electrical & Electronics Lab. Prereq: Phys 117A, and Math 131 or 141. Coreq: CSE 131 or 126, plus MATLAB programming.
E35 - ESE	103	Introduction To Electrical Engineering	1
		A hands-on introduction to electrical engineering to put the FUN into the electrical engineering FUNdamentals. Experiments are designed to be easy to conduct and understand. We will examine some of the technologies used in a variety of applications including the iPod, Ultrasound Imaging, Radar, and Credit Card Readers. We will also hear presentations from the EE faculty about their research.
E45 - ESE	105	Introduction To Electrical & Systems Engineering	3
		A comprehensive introduction to the theory and practice of electrical and sytems engineering. An application area such as multimedia communication systems is used as a theme throughout to motivate the diverse elements of the course, which spans from electronic devices, electrical systems, control systems and operations research. Many fundamental aspects of engineering are covered, including physics and physical devices, mathematical modeling, analytical problem-solving, engineering design, optimization and laboratory experimentation. Course topics and skills are integrated in design projects covering contemporary applications of interest to the instructor and student. Co-requisites: Physics 117A and Math 131
E45 - ESE	107	Introduction To Sustainable Energy	1
		What do you really know about the coming Energy Crunch? What should you know about the coming Energy Crunch? For that matter, what does the Instructor know about the coming Energy Crunch? Probably, in all three cases, not nearly as much as befits a well-informed citizen of our democracy, which is facing one. A fundamental prerequisite for continued existence of our technically rich civilization is Sustainable Energy, energy that will be available even when our dowry of fossil fuels and fissionable elements is only a memory. The purpose of this Course is to attain understanding of the daunting problems which have to be worked through to achieve that Sustainability. Topics will include: Ragone charts; nuclear transformations and gravity as primary energy sources; sunshine, tides, and geothermal heat as secondary energy sources; fossil fuels, biomass, elevated bodies of water, wind, etc. as tertiary energy sources; the electric power grid; load levelling using quaternary energy sources; the slowly approaching Mineral Resource Crunch. The Group will meet an average of one and a half hours a week for provocative discussion of the texts and other reading matter. A short essay (less than 750 words) will be required at the end of the course. Prerequisites: High school biology, chemistry, and physics. Open to levels 1-4; with preference given to lower levels.
E35 - ESE	141	Introductory Robotics	1
		A hands-on introduction to robotics. Project-oriented course where students build and program a robot guided by upper-division students. Friendly competition at the end of semester. Students will gain electrical lab experience, programming experience, and a guided introduction into the field of robotics.
E35 - ESE	145	Computer Control Of A Robot	2
		This course is designed for engineering freshmen. Students learn to control a robot via a personal computer in the Systems Engineering Laboratory. Specifically, they learn the basics of programming, the interface between the computer and the robot, the use of the special software for controlling the interface and ultimately the real-time control of the robot. The course emphasizes team projects in which a group of students develop computer programs for controlling a robot.
E35 - ESE	230	Introduction To Electrical & Electronic Circuits	4
		Electron and ion motion, electrical current and voltage. Electrical energy, current, voltage, and circuit elements. Resistors, Ohm's Law, power and energy, magnetic fields and dc motors. Circuit analysis and Kirchhoff's voltage and current laws. Thevenin and Norton transformations and the superposition theorem. Measuring current, voltage, and power using ammeters and voltmeters. Energy and maximum electrical power transfer. Computer simulations of circuits. Reactive circuits, inductors, capacitors, mutual inductance, electrical transformers, energy storage, and energy conservation. RL, RC and RLC circuit transient responses, biological cell action potentials due to Na and K ions. AC circuits, complex impedance, RMS current and voltage. Electrical signal amplifiers and basic operational amplifier circuits. Inverting, non-inverting, and difference amplifiers. Voltage gain, current gain, input impedance, and output impedance. Weekly laboratory exercises related to the lectures are an essential part of the course. Prerequisites: Phys 118A. Corequisite: Math 217.
E35 - ESE	232	Introduction To Electronic Circuits	3
		Analysis and design of linear electronic circuits. Terminal characteristics of active semiconductor devices. Incremental and DC models for diodes, metal-oxide-semiconductor field effect transistors (MOSFETs), and bipolar junction transistors (BJTs). Design and analysis of single- and multi-stage amplifiers. Volatile and non-volatile semiconductor memories. Understanding of common application circuits in integrated circuit chips. Semester-long design project (e.g., designing circuits to process corrupted audio files). Prerequisite: ESE 230.
E35 - ESE	233	Electrical And Electronics Laboratory	3
		Lectures and laboratory exercises related to sophomore topics in introductory networks and basic electronics. Prerequisite: ESE 230.
E35 - ESE	251	Introduction To Systems Science And Engineering	3
		Introduction to the methodology of systems engineering: mathematical modeling, optimization, utilization of scientific literature. Applications in engineering, sports, medicine, business, etc. Guest lecturers from various disciplines. Student-initiated investigations and presentations. Students are required to keep a log of all lectures and presentations. Grading is based on these logs and on participation in the work of the class. (Not open to seniors or graduate students.) Prerequisite: Math 233, Physics 117A and 118A. Corequisite: Math 217.
E35 - ESE	260	Introduction To Digital Logic And Computer Design	3
		Introduction to design methods for digital logic and fundamentals of computer architecture. Boolean algebra and logic minimization techniques; sources of delay in combinational circuits and effect on circuit performance; survey of common combinational circuit components; sequential circuit design and analysis; timing analysis of sequential circuits; use of computer-aided design tools for digital logic design (schematic capture, hardware description languages, simulation); design of simple processors and memory subsystems; program execution in simple processors; basic techniques for enhancing processor performance; configurable logic devices. Prerequisites: CSE 131/CS 101G or 126/136G or comparable programming experience.
E35 - ESE	309	Matrix Algebra	3
		Operations with matrices, determinants, solution of linear systems, rank, vector spaces, matrices as transformations; eigenvalue problems; normal forms. Prerequisite: Math 132 or equivalent.
E35 - ESE	317	Engineering Mathematics	4
		The Laplace transform and applications; series solutions of differential equations, Bessel's equation, Legendre's equation, special functions; matrices, eigenvalues, and eigenfunctions; vector analysis and applications; boundary value problems and spectral representations; Fourier series and Fourier integrals; solution of partial differential equations of mathematical physics. Prerequisite: Math 217 or equivalent.
E35 - ESE	326	Probability And Statistics For Engineering	3
		Study of probability and statistics together with engineering applications. Probability and statistics: random variables, distribution functions, density functions, expectations, means, variances, combinatorial probability, geometric probability, normal random variables, joint distribution, independence, correlation, conditional probability, Bayes theorem, the law of large numbers, the central limit theorem. Applications: reliability, quality control, acceptance sampling, linear regression, design and analysis of experiments, estimation, hypothesis testing. Examples are taken from engineering applications. Prerequisites: Math 233 or equivalent.
E35 - ESE	330	Engineering Electromagnetics Principles	3
		Electromagnetic theory as applied to electrical engineering: vector calculus; electrostatics and magnetostatics; Maxwell's equations, including Poynting's theorem and boundary conditions; uniform plane-wave propagation; transmission lines, TEM modes, including treatment of general lossless lines, and pulse propagation; introduction to guided waves; introduction to radiation and scattering concepts. Prerequisite: ESE 317, or equivalent.
E35 - ESE	331	Electronics Laboratory	3
		Laboratory exercises for juniors covering topics in computer-aided measurements, computer simulation, and electronic circuits. Prerequisites: ESE 102 ESE 232.
E35 - ESE	332	Power, Energy And Polyphase Circuits	3
		Fundamental concepts of power and energy; electrical measurements; physical and electrical arrangement of electrical power systems; polyphase circuit theory and calculations; principal elements of electrical systems such as transformers, rotating machines, control, and protective devices, their description and characteristics; elements of industrial power system design. Prerequisite: ESE 230.
E35 - ESE	334	Network Analysis	3
		Theoretical and practical aspects of electrical networks. Loop and nodal analysis of multiport networks. Transfer functions, admittance and impedance functions, and matrices. Magnitude and phase relations. Butterworth, Chebyshev, and other useful network response functions. Network theorems. Computer-aided design. Synthesis of passive (LC, RC, RLC) networks and of active (RC) networks. Prerequisite: ESE 260/CSE260M..
E35 - ESE	336	Principles Of Electronic Devices	3
		Introduction to the solid-state physics of electronic materials and devices, including semiconductors, metals, insulators, diodes and transistors. Crystal growth technology and fundamental properties of crystals. Electronic properties and band structure of electronic materials, and electron transport in semiconductor materials. Fabrication of pn junction diodes, metal-semiconductor junctions, and transistors and integrated-circuit chips. Fundamental electrical properties of rectifying diodes and light-emitting diodes, bipolar transistors and field-effect transistors. Device physics of diodes and transistors, large-signal electrical behavior and high-frequency properties. Prerequisite: Phys 118A.
E35 - ESE	337	Electronic Devices And Circuits	3
		Introduction to semiconductor electronic devices: transistors and diodes. Device electrical DC and high-frequency characteristics. Bipolar transistors, field-effect transistors, and MOS transistors for analog electronics applications. Transistor fabrication as discrete devices and as integrated-circuit chips. Large-signal analysis of transistor amplifiers: voltage gain, distortion, input resistance and output resistance. Analysis of multitransistor amplifiers: Darlington, Cascode, and coupled-pair configurations. Half-circuit concepts, differential-mode gain, common-mode gain, and differential-to-single-ended conversion. Transistor current sources, active loads, and power-amplifier stages. Applications to operational amplifiers and feedback circuits. Prerequisite: ESE 232.
E35 - ESE	351	Signals And Systems	3
		Introduction to concepts and methodology of linear dynamic systems in relation to discrete- and continuous-time signals. Representation of systems and signals. Fourier, Laplace, and Z-transforms and convolution. Input-output description of linear systems: impulse response, transfer function. State-space description of linear systems: differential and difference equation description, transition matrix. Time-domain and frequency-domain system analysis: transient and steady-state responses, system modes, stability, frequency spectrum. System design: filter, modulation. Continuity is emphasized from analysis to synthesis and implementation. Use of Matlab. Prerequisites: The notion of Matrix algebra and Math 217 or equivalent, Physics 117A-118A Corequisite: ESE 317.
E35 - ESE	362	Computer Architecture	3

E35 - ESE	400	Independent Study	3
		Opportunities to acquire experience outside the classroom setting and to work closely with individual members of the faculty. A final report must be submitted to the department. Not open to first-year or graduate students. Consult adviser. Hours and credit to be arranged.
E35 - ESE	402	Computer Aided Design Systems	3
		Introduction to computer-aided techniques in the solution of network and electronic design problems, including filters; analysis of linear and nonlinear circuits; methods for numerical integration, evaluation of the Fourier integral; numerical methods for solving differential equations, automated methods for design; sparse matrix techniques. Use of problem-oriented languages such as SPICE. Methods for the analysis and design of digital circuits and systems. Prerequisites: ESE 232, 351.
E35 - ESE	403	Operations Research	3
		Introduction to the mathematical aspects of various areas of operations research, with additional emphasis on problem formulation. This is a course of broad scope, emphasizing both the fundamental mathematical concepts involved, and also aspects of the translation of real-world problems to an appropriate mathematical model. Subjects to be covered include linear and integer programming, network problems, and dynamic programming. Prerequisites: Math 217 and familiarity with matrix or linear algebra, or permission of instructor.
E35 - ESE	404	Applied Operations Research	3
		Application of deterministic and stochastic operations research techniques to real-world problems. Emphasis is given to linear programming and simulation. The nature of the problems ranges from logistics and planning to operations management. The systems to be examined are transportation systems, supply chain systems, medical care delivery systems, urban service systems, management systems, manufacturing systems. Emphasis is placed on the problem formulation of real-world problems, the use of computer software and the analysis of the solutions. Prerequisites: ESE 326 and ESE 403 or equivalent.
E35 - ESE	405	Reliability And Quality Control	3
		An integrated analysis of reliability and quality control function in manufacturing. Statistical process control, acceptance sampling, process capability analysis, reliability prediction, design, testing, failure analysis and prevention, maintainability, availability, and safety are discussed and related. Qualitative and quantitative aspects of statistical quality control and reliability are introduced in the context of manufacturing. Prerequisite: ESE 326 or equivalent.
E35 - ESE	407	Analysis And Simulation Of Discrete Event Systems	3
		Study of the dynamic behavior of discrete event systems and techniques for analyzing and optimizing the performance of such systems. Covers both classical and recent approaches. Classical topics include Markov chains, queuing theory, networks of queues, related algorithms, and simulation methods. Recent approaches include decomposition and aggregation, approximation, and perturbation analysis of nonclassical systems. Applications are drawn from various areas, including production systems. Prerequisites: Math 217, ESE 326 or equivalent, CSE 126 or equivalent.
E35 - ESE	408	A System Dynamics Approach To Designing Sustainable Policies And Programs	3
		Principles and practice of modeling dynamic systems in the sciences, engineering, social sciences, and business. Model structure and its relationships to prior knowledge and assumptions, measurable quantities, and ultimate use in solving problems in application areas. Problems considered are in the areas of intervention, policy-making, business, and engineering systems. Model verification. The basic theory and practice of system dynamics. Quantitative methods are emphasized. Senior or graduate standing.
E35 - ESE	411	Numerical Methods	3
		An introduction to current numerical methods: root finding, direct solution of linear systems, iterative solution of linear systems, interpolation, data fitting, numerical differentiation and integration, application to physical and engineering problems. For graduate credit, a term project is required. Prerequisites: Math 217, CSE 131, 126, or 200 or equivalent, and sophomore standing. Fridays are for makeups.
E35 - ESE	414	Calculus Of Variations	3
		Introduction to the theory and applications of the calculus of variations. Theory of functionals; variational problems for an unknown function; Euler's equation; variable end-point problems; variational problems with subsidiary conditions; sufficient conditions for extrema: applications to optimum control and/or to other fields. For graduate credit, a term project is required. Prerequisite: ESE 317 or equivalent.
E35 - ESE	415	Optimization	3
		Optimization problems with and without constraints. The projection theorem. Convexity, separating hyperplane theorems; Lagrange multipliers, Kuhn-Tucker-type conditions, duality; computational procedures. Optimal control of linear dynamic systems; maximum principles. Use of optimization techniques in engineering design. Prerequisites: ESE 309, or permission of instructor.
E35 - ESE	416	Complex Variables	3
		Introduces analytical functions of a complex variable as a primary tool in the formulation and solution of engineering problems. Topis: Elementary functions, contour integration in the complex plane, power series, residue theory,conformal mapping, Laplace and Fourier inverse transforms, two-dimensional potential theory. Prerequisite: Engineering ESE 317 or equivalent.
E35 - ESE	425	Random Processes And Kalman Filtering	3
		Probability and random variables; random processes; linear dynamic systems and random inputs; autocorrelation; spectral density; the discrete Kalman filter; applications; the extended Kalman filter for nonlinear dynamic systems. Kalman filter design using a computer package, mean square estimation; maximum likelihood; Wiener filtering and special factorization, LQG/LTR control. Prerequisite: ESE 326 and ESE 351 or equivalent.
E35 - ESE	428	Probability	3

E35 - ESE	430	Engineering Electromagnetics Applications	3
		Study of important applications of electromagnetic theory. Solution of electrostatic and magnetostatic problems involving Laplace and Poisson's equations subject to boundary conditions. Maxwell's equations, including boundary conditions for dielectrics and conductors, reflection and transmission characteristics with effects due to losses. Study of guided waves in rectanglar and optical wave guides, including effects of dispersion. S-parameters and transmission networks, including S-matrix properties, relation to impedance, reflection coefficient, VSWR, and Smith chart. Study of antennas, including exposure to terminology and thin-wire antennas. Prerequisite: ESE 330.
E35 - ESE	431	Quantum Electronics	3

E35 - ESE	432	Advanced Analog Electronics	3
		Design and analysis of analog electronic circuits and operational amplifiers for use in control systems, instrumentation and telecommunications. Large-signal analysis of high-power circuits including transfer characteristics, distortion, power efficiency, impedance, and high-frequency behavior. Frequency response, stability and frequency-compensation of multi-stage feedback amplifiers. Fundamental treatment of electronic noise in circuits including thermal noise, shot noise, and 1/f noise. Review of general-purpose op-amps, wideband video op-amps, and high-performance pecision operational amplifiers and chip layout. Linear and nonlinear analog applications, including power-booster amplifiers, precision rectifiers, differentiators, integrators, phase-locked loops, high-frequency analog multipliers, and mixers. Prerequisite: ESE 337.
E35 - ESE	433	Radio Frequency And Microwave Technology For Wireless Systems	3
		Focus is on the components and associated techniques employed to implement analog and digital radio frequency (RF) and microwave (MW) transceivers for wireless applications, including: cell phones; pagers; wireless local area networks; global positioning satellite based devices; and RF identification systems. A brief overview of system-level considerations is provided, including modulation and detection approaches for analog and digital systems; multiple-access techniques and wireless standards; and transceiver architectures. Focus is on RF and MW: transmission lines; filter design; active component modeling; matching and biasing networks; amplifier design; and mixer design. Prerequisite: ESE 330.
E35 - ESE	434	Solid State Power Circuits And Applications	3
		Study of the strategies and applications power control using solid-state semiconductor devices. Survey of generic power electronic converters. Applications to power supplies, motor drives, and consumer electronics. Introduction to power diodes, thyristors, and MOSFETs. Prerequisites: ESE 232, 351.
E35 - ESE	435	Electrical Energy Laboratory	3
		Experimental studies of principles important in modern electrical energy systems. Topics include: power measurements, single-phase transformers, batteries, three-phase circuits and transformers, static frequency converters, thermoelectric cooling, solar cells, electrical lighting, induction, commutator, and brushless motors, and synchronous machines. Prerequisites: ESE 230 and 232
E35 - ESE	436	Advanced Electronic Devices	3
		The physics of state-of-the-art electronic devices. Devices to be studied include novel diode structures (light-emitting diodes, semiconductor laser diodes), high-power devices (SCRs, TRIACs, and power transistors), and high-speed devices. High-speed devices include heterojunction bipolar (HBT), heterojunction field-effect (HFET), and high electron mobility (HEMT) transistors used in very high-speed systems (up to 100 GHz). Advanced bipolar transistors (poly-Si), used in high-speed microprocessors, examined; also materials properties, transport mechanisms, band structure, and physics of these devices. Prerequisite: ESE 336.
E35 - ESE	437	Sustainable Energy Systems	3
		We will survey the field of sustainable energy and explore current and future contributions within electrical and systems engineering. Specific areas and selected topics include energy distribution and storage, smart and robust power grids, energy and building efficiency, energy conversion, photovoltaics, and control of wind turbines. The course will consist of lectures, laboratory experiments, review and discussion of literature, and student projects. Prerequisite: ESE 317 and junior or senior standing, or permission of the instructor.
E35 - ESE	438	Applied Optics	3
		Topics relevant to the engineering and physics of conventional as well as experimental optical systems and applications explored. Items addressed include geometrical optics, Fourier optics such as diffraction and holography, polarization and optical birefringence such as liquid crystals, and nonlinear optical phenomena and devices. Prerequisite: ESE 330 or equivalent.
E35 - ESE	441	Control Systems	3
		Introduction to theory and practice of automatic control for continuous-time systems. Representations of the system: transfer function, block diagram, signal flow graph, difference and differential state equation and output equation. Analysis of control system components. Transient and steady-state performance. System analysis: Routh-Hurwitz, root-locus, Nyquist, Bode plots. System design: PID controller, and lead-lag compensators, pole placement via state feedback, observer, stability margins in Nyquist and Bode plots. Emphasis on design principles and their implementation. Design exercises with a MATLAB package for specific engineering problems. Prerequisites: ESE 351 or MASE 431.
E35 - ESE	442	Digital Control Systems	3
		The control of physical systems with digital computer, microprocessor, or special-purpose digital hardware is becoming very common. Course continues ESE 441 to develop models and mathematical tools needed to analyze and design these digital, feedback-control systems. Linear, discrete dynamic systems. The Z-transform. Discrete equivalents to continuous transfer functions. Sampled-data control systems. Digital control systems design using transfer and state-space methods. Systems composed of digital and continuous subsystems. Quantization effects. System identification. Multivariable and optimum control. Prerequisite: ESE 351 and 441 (or MAE 431) or permission of instructor.
E35 - ESE	443	Control Systems Design By State Space Methods	3
		Advanced design and analysis of control systems by state-space methods: review of linear algebra (vector space, change of basis, diagonal and Jordan forms), linear dynamic systems (modes, stability, controllability, state feedback, observability, observers, canonical forms, output feedback, separation principle and decoupling), nonlinear dynamic systems (stability, Lyapunov methods), approximate linearization feedback linearization. Design exercises with CAD (computer-aided design) packages for engineering problems. Prerequisite: ESE 351, or MAE 417, or permission of instructor. ESE 543 requires a project.
E45 - ESE	444	Sensors And Actuators	3
		The course provide engineering students with basic understanding of two of the main components of any modern electrical or electromechanical system; sensors as inputs and actuators as outputs. The covered topics include transfer functions, frequency responses and feedback control. Component matching and bandwidth issues. Performance specification and analysis, Sensors: analog and digital motion sensors, optical sensors, temperature sensors, magnetic and electromagnetic sensors, acoustic sensors, chemical sensors, radiation sensors, torque, force and tactile sensors. Actuators: stepper motors, DC and AC motors, hydraulic actuators, magnet and electromagnetic actuators, acoustic actuators. Introduction to interfacing methods: bridge circuits, A/D and D/A converters, microcontrollers. This course is useful for those students interested in control engineering, robotics and systems engineering. Prerequisites: one of the following 4 conditions: (1) prerequisite of ESE 230 and corequisite of ESE 351; (2) prerequisites of ESE 230, ESE 317 and MASE 255 (Mechanics II); (3) prerequisites of ESE 105/251 and ESE 351; (4) permission of instructor.
E35 - ESE	446	Robotics: Dynamics And Control	3
		Homogeneous coordinates and transformation matrices. Kinematic equations and the inverse kinematic solutions for manipulators, the manipulator Jacobian and the inverse Jacobian. General model for robot arm dynamics, complete dynamic coefficients for six-link manipulator. Synthesis of manipulation control, motion trajectories, control of single- and multiple-link manipulators, linear optimal regulator. Model reference adaptive control, feedback control law for the perturbation equations along a desired motion trajectory. Design of the control system for robotics. Prerequisites: ESE 317, 351 or 441, and knowledge of a programming language.
E35 - ESE	447	Robotics Laboratory	3
		Introduces the students to various concepts such as modeling, identification, model validation and control of robotic systems. The course focuses on the implementation of identification and control algorithms on a two-link robotic manipulator (the so-called pendubot) that will be used as an experimental testbed. Topics include: Introduction to the mathematical modeling of robotic systems; nonlinear model, linearized model; Identification of the linearized model: input-output and state-space techniques; Introduction to the identification of the nonlinear model: energy-based techniques; model validation and simulation; stabilization using linear control techniques; a closer look at the dynamics; stabilization using nonlinear control techniques. Prerequisite: ESE 351 or MAE 417.
E35 - ESE	448	Systems Engineering Laboratory	3
		Experimental study of real and simulated systems and their control. Identification, input-output analysis, design and implementation of control systems. Noise effects. Design and implementation of control laws for specific engineering problems. Corequisite: ESE 441 and knowledge of a programming language.
E35 - ESE	449	Digital Process Control Laboratory	3
		Applications of digital control principles to laboratory experiments supported by a networked distributed control system. Lecture material reviews background of real-time programming, data acquisition, process dynamics, and process control. Exercises in data acquisition and feedback control design using simple and advanced control strategies. Experiments in flow, liquid level, temperature, and pressure control. Term project. Prerequisite: ESE/ME 441 or equivalent. Co-requisite: ChE 462 or equivalent.
E35 - ESE	460	Switching Theory	3

E35 - ESE	462	Computer Systems Design	3

E35 - ESE	463	Digital Integrated Circuit Design And Architecture	3

E35 - ESE	464	Digital Systems Engineering	3

E35 - ESE	465	Digital Systems Laboratory	3

E35 - ESE	467	Embedded Computing Systems	3

E35 - ESE	471	Communications Theory And Systems	3
		Introduction to the concepts of transmission of information via communication channels. Amplitude and angle modulation for the transmission of continuous-time signals. Analog-to-digital conversion and pulse code modulation. Transmission of digital data. Introduction to random signals and noise and their effects on communication. Optimum detection systems in the presence of noise. Elementary information theory. Overview of various communication technologies such as radio, television, telephone networks, data communication, satellites, optical fiber, and cellular radio. Prerequisites: ESE 351 and ESE 326.
E35 - ESE	482	Digital Signal Processing	3
		Introduction to analysis and synthesis of discrete-time linear time-invariant (LTI) systems. Discrete-time convolution, discrete-time Fourier transform, z-transform, rational function descriptions of discrete-time LTI systems. Sampling, analog-to-digital conversion, and digital processing of analog signals. Techniques for the design of finite impulse response (FIR) and infinite impulse response (IIR) digital filters. Hardware implementation of digital filters and finite-register effects. The Discrete Fourier Transform and the Fast Fourier Transform (FFT) algorithm. Prerequisite: ESE 351.
E35 - ESE	483	Medical Imaging	3
		Introduction to the mathematical, physical and engineering principles underlying modern medical imaging systems including x-ray computed tomography, ultrasonic imaging, and magnetic resonance imaging. Mathematical tools including Fourier analysis and the sampling theorem; the Radon transform and related transforms; reconstitution algorithms for computed tomography; tomographic imaging with diffracting sources; Bloch equations; free induction decay, spin echos and gradient echoes; one-dimensional Fourier magnetic resonance imaging; three-dimensional magnetic resonance imaging and slice excitation. ESE 583 requires a project. Prerequisite: ESE 351
E35 - ESE	488	Signals And Systems Laboratory	3
		A laboratory course designed to complement the traditional EE course offerings in signal processing, communication theory, and automatic control. Signals and systems fundamentals: continuous-time and discrete-time linear time-invariant systems, impulse and step response, frequency response, A/D and D/A conversion. Digital signal processing: FIR and IIR digital filter design, implementation and application of the Fast Fourier Transform. Communication theory: baseband, digital communication, amplitude modulation, frequency modulation,bandpass digital communication. Automatic control: system modeling, feedback control systems, closed-loop transient and frequency response. Laboratory experiments involve analog and digital electronics, and mechanical systems. Computer workstations and modern computational software used extensively for system simulation, real-time signal processing, and discrete-time automatic control. Prerequisite: ESE 351.
E45 - ESE	489	Biological Imaging Technology	3
		This class will develop a fundamental understanding of the physics and mathematical methods that underlie biological imaging and critically examine case studies of seminal biological imaging technology literature. The physics section will examine how electromagnetic and acoustic waves interact with tissues and cells, how waves can be used to image the biological structure and function, image formation methods and diffraction limited imaging. The math section will examine image decomposition using basis functions (e.g. fourier transforms), synthesis of measurement data, image analysis for feature extraction, reduction of multi-dimensional imaging datasets, multivariate regression, and statistical image analysis. Original literature on electron, confocal and two photon microscopy, ultrasound, computed tomography, functional and structural magnetic resonance imaging and other emerging imaging technology will be critiqued.
E35 - ESE	497	Undergraduate Research	3
		Undergraduate research under the supervision of a faculty member. A written final report and a Web page describing the research are required
E35 - ESE	498	Electrical Engineering Design Projects	3
		Working in teams, students address design tasks assigned by faculty. Each student participates in one or more design projects in a semester. Projects are chosen to emphasize the design process, with the designers choosing one of several paths to a possible result. Collaboration with industry and all divisions of the University is encouraged. Prerequisite: senior standing.
E35 - ESE	499	Systems Design Project	3
		Term design project, directed by a faculty adviser, requiring use of systems theory, techniques, engineering, and concepts. This project is carried out in cooperation with either local industry or university laboratories. The solution of a real technological or societal problem is carried through completely, starting from the stage of initial specification, proceeding with the application of systems engineering methods, and terminating with an actual solution. Required documents are a written proposal and a final report on the project. An oral presentation of the project also is required. Prerequisite: SSE senior standing.
E35 - ESE	500	Independent Study	3
		Opportunities for graduate students to explore possible areas of interest with individual faculty members. Coordinated study programs dealing with areas not covered by formal course work are possible. Independent study credit can be changed to research credit (ESE 599) any time during the semester if enrollment is appropriate. A final report is required to be submitted to the Department.
E35 - ESE	501	Mathematics Of Modern Engineering I	3
		Vectors and vector spaces, Matrix operations, System of linear equations, Eigenvalues and eigenvectors, Vector fields, Line and surface integrals, Solutions to ordinary and partial differential equations, Series expansions, Fourier Series. Prerequisite:ESE 317 or equivalent or consent of instructor.
E35 - ESE	502	Mathematics Of Modern Engineering II	3
		Techniques of solving ordinary differential equations with constant coefficients, Laplace's Transform, solutions for the heat and wave equations, Laplace's Equation, Legendre and Bessel Function, Introduction to function of a complex variable, conformal mapping, contour integrals. Prerequisite: ESE 317 or equivalent, or consent of instructor.
E35 - ESE	503	Operations Research	3
		Introduction to the mathematical aspects of various areas of operations research, with additional emphasis on problem formulation. This is a course of broad scope, emphasizing both the fundamental mathematical concepts involved, and also aspects of the translation of real-world problems to an appropriate mathematical model. Subjects to be covered include linear and integer programming, network problems and dynamic programming. Prerequisites: Math 217 and familiarity with matrix or linear algebra, or permission of instructor.
E35 - ESE	505	Reliability And Quality Control	3
		An integrated analysis of reliability and quality control function in manufacturing. Statistical process control, acceptance sampling, process capability analysis, reliability prediction, design, testing, failure analysis and prevention, maintainability, availability, safety, and design review are discussed and related. Qualitative and quantitative aspects of statistical quality control and reliability are introduced in the context of manufacturing. Prerequisites: ESE 326 or equivalent. Same as ESE 405. ESE 505 requires a project.
E35 - ESE	508	Dynamic Systems Modeling	3
		Principles and practice of modeling dynamic systems in the sciences, engineering, social sciences, and business. Model structure and its relationships to prior knowledge and assumptions, measurable quantities, and ultimate use in solving problems in application areas. Problems considered are in the areas of intervention, policy-making, business, and engineering systems. Model verification. The basic theory and practice of system dynamics. Quantitative methods are emphasized. Graduate standing is required.
E45 - ESE	508	Dynamic Systems Modeling	3
		Principles and practice of modeling dynamic systems in the sciences, engineering, social sciences, and business. Model structure and its relationships to prior knowledge and assumptions, measurable quantities, and ultimate use in solving problems in application areas. Problems considered are in the areas of intervention, policy-making, business, and engineering systems. Model verification. The basic theory and practice of system dynamics. Quantitative methods are emphasized. Graduate standing is required.
E35 - ESE	511	Numerical Analysis	3
		An introduction to current numerical methods: root finding, direct solution of linear systems, iterative solution of linear systems, interpolation, data fitting, numerical differentiation and integration, application to physical and engineering problems. For graduate credit, a term project is required. Prerequisites: Math 217, CSE 131, 126 or 200 or equivalent, and sophomore standing.
E35 - ESE	512	Advanced Numerical Analysis	3
		Special topics to be chosen from numerical solution of partial differential equations, uniform and least-squares approximation spline approximation, Galerkin methods and finite element approximation, functional analysis applied to numerical mathematics, and other topics of interest. Prerequisite: ESE 511 or consent of instructor.
E35 - ESE	513	Nonlinear Methods In Engineering	3
		Nonlinear methods not treated in traditional engineering courses are applied to diverse engineering problems. Presented is method sorting by assessing the problem Double Scroll circuit, population dynamics, laser beam competition and electrocardiograms by chaotic dynamics and phase plane analysis with computer simulations. The nonlinear ion acoustic fluid equations are simplified by perturbation expansions. Plasma etching in the fabrication of integrated circuits is solved by the method of characteristics. Higher symmetry applications include the submarine explosion equation, the Debye-Huckel equation in electrolytes and the magnetic domain equation and exact solutions are found by Lie group methods. This method is aided by computer programs such as LIE and Mathematica. Optical solitons in optical fibers, ion acoustic solitons in plasmas and solitons in Josephson junction transmission lines demonstrate the 3 fundamental soliton equations and their useful applications.
E35 - ESE	514	Calculus Of Variations	3
		Introduction to the theory and applications of the calculus of variations. Theory of functionals; variational problems for an unknown function; Euler's equation; variable end-point problems; variational problems with subsidiary conditions; sufficient conditions for extrema: applications to optimum control and/or to other fields. Same as ESE 414. For graduate credit, a term project is required. Prerequisite: ESE 317 or equivalent.
E35 - ESE	515	Optimization	3
		Optimization problems with and without constraints. The projection theorem. Convexity, separating hyperplane theorems; Lagrange multipliers, Kuhn-Tucker-type conditions, duality; computational procedures. Optimal control of linear dynamic systems; maximum principles. Use of optimization techniques in engineering design. Note: This course is the same as ESE 415 but requires a term project. Prerequisites: ESE 309 and 403, or permission of instructor.
E35 - ESE	516	Optimization In Function Space	3
		Linear vector spaces. Normed linear spaces. Lebesque integrals. The Lp spaces. Linear operators. Dual spaces. Hilbert spaces. Projection theorem. Hahn-Banach theorem. Hyperplanes and convex sets. Gateaux and Fr�chet differentials. Unconstrained minima. Adjoint operators. Inverse function theorem. Constrained minima. Equality constraints. Lagrange multipliers. Calculus of variations. Euler-Lagrange equations. Positive cones. Inequality constraints. Kuhn-Tucker theorem. Optimal control theory. Pontryagin's maximum principle. Successive approximation methods. Newton's methods. Steepest descent methods. Primal-dual methods. Penalty function methods. Multiplyer methods. Prerequisite: Math 411.
E35 - ESE	517	Partial Differential Equations	3
		Linear and nonlinear first order equations. Characteristics. Classification of equations. Theory of the potential linear and nonlinear diffusion theory. Linear and nonlinear wave equations. Initial and boundary value problems. Transform methods. Integral equations in boundary value problems. Prerequisite: ESE 317 or equivalent or consent of instructor.
E35 - ESE	520	Probability And Stochastic Processes	3
		Review of probability theory, models for random signals and noise, calculus of random processes, noise in linear and nonlinear systems, representation of random signals by sampling and orthonormal expansions. Poisson, Gaussian, and Markov processes as models for engineering problems. Prereq: ESE 326.
E35 - ESE	521	Random Variables And Stochastic Processes I	3
		Mathematical foundations of probability theory, including constructions of measures, Lebesque-measure, Lebesque-integral, Banach space property of Lp, basic Hilbert-space theory, conditional expectation. Kolmogorov's theorems on existence and sample-path continuity of stochastic processes. An in-depth look at the Wiener process. Filtrations and stopping times. Markov processes and diffusions, including semigroup properties and the Kolmogorov forward and backward equations. Prerequisites:ESE 520 or equivalent, Math 411.
E35 - ESE	522	Random Variables And Stochastic Processes II	3
		Review of probability theory. Conditional probability and conditional expectation. Discrete parameter martingales. Brownian motion. Ito's stochastic calculus and continuous parameter martingales. Ito type stochastic differential equations and Markov processes. Stability problems of stochastic dynamic systems. Stochastic control and filtering of linear systems. Prerequisites: ESE 520 and Math 409 or equivalent.
E35 - ESE	523	Information Theory	3
		Discrete source and channel model, definition of information rate and channel capacity, coding theorems for sources and channels, encoding and decoding of data for transmission over noisy channels. Corequisite: ESE 520.
E35 - ESE	524	Detection And Estimation Theory	3
		Study of detection, estimation and modulation theory, detection of signals in noise, estimation of signal parameters, linear estimation theory. Kalman-Bucy and Wiener filters, nonlinear modulation theory, optimum angle modulation. Prerequisite: ESE 520.
E35 - ESE	525	Random Processes And Kalman Filtering	3
		Probability and random variables; random processes; linear dynamic systems and random inputs; the discrete Kalman filter; applications; the extended Kalman filter for nonlinear dynamic systems. Kalman filter design using a computer package. Prerequisites: ESE 326 and (ESE 543 or ESE 551) or permission of instructor. (This course is the same as ESE 425 but requires a term project.) There will be computer assignments.
E35 - ESE	529	Special Topics In Information Theory And Applied Probability	3

E35 - ESE	531	Nano And Micro Photonics	3
		This course focuses on theory, design, fabrication and application of photonic materials and micro/nano photonic devices. Interaction of light and matter, propagation of light in waveguide, nonlinear optical effect and optical properties of nano/micro structure, the device principles of silicon-based waveguide, filter, photodetector, modulator and laser devices. Prerequisite: ESE 330.
E45 - ESE	531	Nano And Micro Photonics	3
		This course focuses on theory, design, fabrication and application of photonic materials and micro/nano photonic devices. Interaction of light and matter, propagation of light in waveguide, nonlinear optical effect and optical properties of nano/micro structure, the device principles of silicon-based waveguide, filter, photodetector, modulator and laser devices. Prerequisite: ESE 330.
E35 - ESE	532	Introduction To Nano-photonic Devices	3
		Introduction to photon transport in nano-photonic devices. This course focuses on the following topics: light and photons, statistical properties of photon sources, temporal and spatial correlations, light-matter interactions, optical nonlinearity, atoms and quantum dots, single- and two-photon devices, optical devices, and applications of nano-photonic devices in quantum and classical computing and communication. Prerequisite: ESE 330 and Physics 217, or permission of instructor.
E35 - ESE	533	Radio Frequency And Microwave Technology For Wireless Systems	3

E35 - ESE	534	Physical Microelectronics	3
		A survey of the materials and technologies of microelectronic devices and processing. Review of solid state physics pertinent to materials discussion, particularly thin films. Materials deposition techniques including bulk crystal growth and vapor deposition; device fabrication techniques; materials characterization methods; surfaces, interfaces and contacts; device packaging; device cost and performance issues. Prerequisite: ESE 336.
E35 - ESE	535	Magnetic Recording Technology	3
		Basic concepts: magnetic fields, magnetization, coercivity, hysteresis; write and read processes, reciprocity. Recording materials: particulate and continuous film media. Recording heads: ring pole; ferrite, thin film; inductive, magneto-resistive. Analog recording: high-frequency bias, audio and video systems, noise. Digital recording: coding distortion, bit shift, equalization; rigid disk, flexible disk, tape drives. Nascent technologies: perpendicular, isotropic media; magneto-optic, reversible-optical storage. Prerequisite: ESE 330.
E35 - ESE	536	Plasma Applications	3
		This course introduces basic properties of plasmas which include Debye-Huckel screening and electromagnetic effects. Single-particle motion, small-amplitude waves and motion in magnetized plasmas in the fluid approximation, particle distribution functions and discharge plasmas are treated. Emphasis is on engineering applications such as propagation of radio waves in the earth's ionosphere,satellite communication, plasma propulsion and magnetohydrodynamic power. The principal application is plasma processing: ionbeam sputtering of surfaces and plasma etching and deposition on semiconductor wafers used to fabricate integrated circuits Prerequisite: ESE 330.
E35 - ESE	537	Advanced Electromagnetic Theory	3
		Solution of electromagnetic boundary value problems, applications to engineering analysis and design. First semester: mathematical methods for electro-statics, magnetostatics, and electrodynamics, emphasizing Green's function techniques. Second semester: radiation and diffraction; waveguides, antennas, and optics. Vector boundary conditions, Green's dyadics, variational techniques. Prerequisites: advanced calculus, ESE 430, or equivalent.
E35 - ESE	538	Advanced Electromagnetic Engineering	3
		This course begins with a brief review of prerequisite topics. The following topics will be treated for guided-wave systems: solution for and use of mode sets in planar and cylindrical guided-wave systems; use of alternative mode sets for inhomogeneous guided-wave systems; dielectric-based and surface-guided wave systems. Methods for launching waves in systems will be studied, including: modal expansions, current-based launchers using electric or magnetic coupling techniques, and aperture excitation. Perturbational and variational methods will be studied for representing important characteristics of guided-wave and resonator systems. Modal expansions will be related to a one- and two-port microwave network treatment of obstacles and circuit elements and junctions in guide-wave systems. The course will then shift to the study of modern numerical methods for developing frequency- and time-domain solutions for guided-wave and two-dimensional radiation and scattering problems encountered in electromagnetic engineering applications. The methods learned will be applied to a project selected and carried-out by each student. Course prerequisites: Equivalent of ESE 330, ESE 430, and ESE 537 or instructor permission
E35 - ESE	538A	Applied Optics	3
		Topics relevant to the engineering and physics of conventional as well as experimental optical systems and applications explored. Items addressed include geometrical optics, Fourier optics such as diffraction and holography, polarization and optical birefringence such as liquid crystals, and nonlinear optical phenomena and devices. Prerequisite: ESE 330 or equivalent.
E45 - ESE	539	Advanced Electromagnetics: Radiation And Scattering	3
		This course starts with a brief review of fundamental concepts including: wave behavior, the generalized source concept, basics of radiation, duality, uniqueness, image theory, the equivalence principle and reciprocity. The focus then turns to important definitions of antenna parameters and qualities. Important antenna types are addressed, including resonant and traveling-wave types. Linear and two-dimensional arrays are treated. Phased-array and active-aperture systems are described. Finally, smart antenna concepts will be presented. Prerequisites: ESE 330 or equivalent.
E35 - ESE	541	Control Systems	3
		Introduction to theory and practice of automatic control for both discrete- and continuous-time systems. Representations of the system: transfer function, block diagram, signal flow graph, difference and differential state equation and output equation. Analysis of control system components. Transient and steady-state performance. System analysis: Routh-Hurwitz, root-locus, Nyquist, Bode plots. System design: PID controller, phase-lead, phase-lag, and lead-lag compensators, pole placement via state feedback, observer, stability margins in Nyquist and Bode plots. Emphasis on design principles and their implementation. Design exercises with a CAD (computer-aided design) package for specific engineering problems. Prerequisite: ME 417, ESE 351 or permission of instructor.
E35 - ESE	543	Control Systems Design By State Space Methods	3
		Advanced design and analysis of control systems by state-space methods: review of linear algebra (vector space, change of basis, diagonal and Jordan forms), linear dynamic systems (modes, stability, controllability, state feedback, observability, observers, canonical forms, output feedback, separation principle and decoupling), nonlinear dynamic systems (stability, Lyapunov methods, approximate linearization, feedback linearization). Design exercises with CAD (computer-aided design) packages for engineering problems. Prerequisite: MAE 417, ESE 351, or permission of instructor.
E35 - ESE	544	Optimization And Optimal Control	3
		Constrained and unconstrained optimization theory. Continuous time as well as discrete-time optimal control theory. Time-optimal control, bang-bang controls and the structure of the reachable set for linear problems. Dynamic programming, the Pontryagin maximum principle, the Hamiltonian-Jacobi-Bellman equation and the Riccati partial differential equation. Existence of classical and viscosity solutions. Application to time optimal control, regulator problems, calculus of variations, optimal filtering and specific problems of engineering interest. Prerequisites: ESE 551, ESE 552.
E35 - ESE	545	Stochastic Control	3
		Introduction to the theory of stochastic differential equations based on Wiener processes and Poisson counters, and an introduction to random fields. The formulation and solution of problems in nonlinear estimation theory. The Kalman-Bucy filter and nonlinear analogues. Identification theory. Adaptive systems. Applications. Prerequisites: ESE 520 and ESE 551
E45 - ESE	545	Stochastic Control	3
		Introduction to the theory of stochastic differential equations based on Wiener processes and Poisson counters, and an introduction to random fields. The formulation and solution of problems in nonlinear estimation theory. The Kalman-Bucy filter and nonlinear analogues. Identification theory. Adaptive systems. Applications. Prerequisites: ESE 520 and ESE 551
E35 - ESE	548	Instruments And Components For Automatic Control	3
		Review of sensor and actuator technologies. Sensor technologies encompass the physical entities to be measured and the corresponding measurement techniques,and actuator technologies cover electrical and hydraulic power actuators. Typical measurements include: position, temperature, pressure, inertial and relative motion, deformation and proximity. The course will also cover the modern class of smart sensors, which include a transducer, some form of digital intelligence, and integrated input/output interfaces. These sensors exhibit chip level integration of micromachining, micromechanical, and microelectronic technologies. Realization of classical sensor techniques in semiconductor form are analyzed. Amplification and signal conditioning at the microcircuit level required to interface sensors with on-chip microprocessors are presented, as well as the current and anticipated communication protocols used in communication within contemporary automotive and industrial control systems. Throughout, emphasis will be given to the specification, selection and application of instruments and sensors to realize fully functional and economical control systems. Prerequisite: ESE 441 or equivalent. (Offered in response to student interest.)
E35 - ESE	549	Special Topics In Control	3

E35 - ESE	551	Linear Dynamic Systems I	3
		Input-output and state-space description of linear dynamic systems. Solution of the state equations and the transition matrix. Controllability, observability, realizations, pole-assignment, observers and decoupling of linear dynamic systems. Prereq: ESE 351.
E35 - ESE	552	Linear Dynamic Systems II	3
		Least squares optimization problems. Riccati equation, terminal regulator, and steady state regulator. Introduction to filtering and stochastic control. Advanced theory of linear dynamic systems. Geometric approach to the structural synthesis of linear multivariable control systems. Disturbance decoupling, system invertibility and decoupling, extended decoupling and the internal model principle. Prerequisite: ESE 551.
E35 - ESE	553	Nonlinear Dynamic Systems	3
		State space and functional analysis approaches to nonlinear systems. Questions of existence, uniqueness, and stability; Lyapunov and frequency-domain criteria; w-limits and invariance, center manifold theory and applications to stability, steady state response and singular perturbations. Poincare-Bendixson theory, the van der Pol oscillator and the Hopf Bifurcation theorem. Prerequisite: ESE 551.
E35 - ESE	554	Nonlinear Feedback Systems	3
		Feedback and feedforward loops are the way that simpler systems are interconnected to design or analyze important complex systems. This architecture underlies the analysis of many modern electronic and mechanical systems and is now becoming more attractive as a tool in communications, neurosciences and systems biology. In this course, we will study the behavior of nonlinear feedback and feedforward systems, paying particular attention to the use of feedback mechanisms to shape the behavior of complex systems. In particular, we will study the sense in which a nonlinear system can exhibit a stable, steady-state behavior in both an equilibrium and a nonequilibrium setting. The lectures will combine an intuitive approach with a careful delineation between what we would hope would occur and what can be established rigorously, illustrated in a variety of applications. Prerequisite: ESE 441/541.
E35 - ESE	556	Computational Methods In Systems	3
		Introduction to numerical techniques for the computational solution of problems arising in the study of systems. Classical methods are first presented to serve as a basis for specialized techniques designed for systems problems. Topics are: Matrix and vector norms, direct and iterative solution of linear equations, interpolation, Householder and Givens transformations, pseudo inverse, eigenvalues and eigenvectors, Schur normal form, Singular value decomposition, Computation of controllability and observability spaces, solution of algebraic Lyapunov and Riccati equations. Prerequisites: Linear or Matrix Algebra, graduate standing or permission of instructor.
E35 - ESE	559	Special Topics In Systems	3

E35 - ESE	560	Computer Systems Architecture I	3

E35 - ESE	561	Computer Systems Architecture II	3

E35 - ESE	565	Acceleration Of Algorithms In Reconfigurable Logic	3

E35 - ESE	566	Reconfigurable System-on-chip Design	3

E35 - ESE	567	Computer Systems Analysis	3

E35 - ESE	569	Parallel Architectures And Algorithms	3

E35 - ESE	570	Coding Theory	3
		Introduction to the algebra of finite fields. Linear block-codes, cyclic codes, BCH and related codes for error detection and correction. Encoder and decoder circuits and algorithms. Spectral descriptions of codes and decoding algorithms. Code performances.
E35 - ESE	571	Transmission Systems And Multiplexing	3
		Transmission and multiplexing systems are essential to providing efficient point-to-point communication over distance. This course introduces the principles underlying modern analog and digital transmission and multiplexing systems and covers a variety of system examples.
E35 - ESE	572	Signaling And Control In Communication Networks	3
		The operation of modern communications networks is highly dependent on sophisticated control mechanisms that direct the flow of information through the network and oversee the allocation of resources to meet the communication demands of end users. This course covers the structure and operation of modern signaling systems and addresses the major design trade-offs which center on the competing demands of performance and service flexibility. Specific topics covered include protocols and algorithms for connection establishment and transformation, routing algorithms, overload and failure recovery and networking dimensioning. Case studies provide concrete examples and reveal the key design issues. Prerequisites: Graduate standing and permission of instructor.
E35 - ESE	574	Digital Communications	3
		Representation of signals by orthonormal expansion, spectral characteristic of digitally modulated signals, channel models, source models, results from information theory, efficient signaling with coded waveforms, intersymbol interference, equalization, optimum demodulation, decoding (including Viterbi decoder), probability of error, carrier and symbol synchronization, spread-spectrum methods. Corequisite: EE551A.
E35 - ESE	575	Fiber-optic Communications	3
		Introduction to optical communications via glass-fiber media. Pulse-code modulation and digital transmission methods, coding laws, receivers, bit-error rates. Types and properties of optical fibers; attenuation, dispersion, modes, numerical aperture. Light-emitting diodes and semiconductor laser sources; device structure, speed, brightness, modes, electrical properties, optical and spectral characteristics. Prerequisites: ESE 330, 336.
E35 - ESE	577	Design And Analysis Of Switching Systems	3

E35 - ESE	578	Digital Representation Of Signals	3
		This course addresses the representation of real-world analog signals in digital forms and is intended to give students a broad introduction to the subject followed by practical illustration of the basic concepts. Analog signals of differing characteristics, such as the electrocardiogram, voice, audio, images, and video are considered and appropriate digitizing and coding techniques are described. Both lossless and lossy coding for data compression are covered as is the reconstruction of analog signals that approximate the original signal. Existing standards for data compression will be studied, with emphasis on the basic concepts leading to such standards. Prerequisite: Graduate standing.
E35 - ESE	579	Special Topics: Signal & Image Processing (digital Representation Of Signals)	3
		This course addresses the representation of real-world analog signals in digital forms and is intended to give students a broad introduction to the subject followed by practical illustration of the basic concepts. Analog signals of differing characteristics, such as the electrocardiogram, voice, audio, images, and video are considered and appropriate digitizing and coding techniques are described. Both lossless and lossy coding for data compression are covered as is the reconstruction of analog signals that approximate the original signal. Existing standards for data compression will be studied, with emphasis on the basic concepts leading to such standards. Prerequisite: Graduate standing.
E35 - ESE	580	Adaptive Filtering	3
		The processing of signals using discrete time adaptive filters designed to minimize squared errors. Transversal filter, lattice filter, and systolic array structures. Linear predictors, Wiener filters, Kalman filters,the LMS algorithm, recursive least squares (RLS) algorithms. Convergence analysis for LMS and RLS algorithms. Special topics. Applications include adaptive beam forming, communication systems, and spectrum estimation.
E35 - ESE	581	Radar Systems	3
		An introduction to the selection and processing of radar signals. Signal design for improving range and doppler resolution, ambiguity functions, chirp and stepped-frequency waveforms, pulse-compression codes. Statistical models for radar data: range-spread, doppler-spread, doubly spread reflectors. Matched-filter and estimator-correlator receivers for range and doppler estimation. Tracking. Multiantenna radar-receivers: interference rejection, adaptive cancelling. Delay-doppler radar-imaging using synthetic-aperture processing. Prerequisite: ESE 524.
E35 - ESE	583	Medical Imaging	3
		ESE 583 requires a project and permission of the instructor.
E35 - ESE	584	Statistical Signal Processing For Sensor Arrays	3
		Methods for signal processing and statistical inference for data acquired by an array of sensors, such as those found in radar, sonar, and wirelesss communications systems. Multivariate statistical theory with emphasis on the complex multivariate normal distribution. Signal estimation and detection in noise with known statistics, signal estimation and detection in noise with unknown statistics, direction finding, spatial spectrum estimation, beamforming, parametric maximum-likelihood techniques. Subspace techniques, including MUSIC and ESPRIT. Performance analysis of various algorithms. Advanced topics may include structured covariance estimation, wideband array processing, array calibration, array processing with polarization diversity, and space-time adaptive processing (STAP). Prereq: ESE 520, ESE 524, linear algebra, computer programming.
E35 - ESE	585	Optical Imaging	3
		A modern introduction to optical imaging. Topics will include: propagation of waves, diffraction, scattering theory, multiple scattering and radiative transport, diffuse light, inverse scattering and other inverse problems, near-field optics. Applications to biomedical problems will be discussed. Prerequisites: ESE 330 and ESE 351.
E35 - ESE	586	Tomographic Systems	3
		The study of systems for imaging the interior of an object from external measurements. Mathematical preliminaries: multidimensional linear-systems, the Poisson process, maximum-likelihood estimation. Transmission, emission, reflection, and magnetic-resonance tomography. Line integral, strip integral, weighted-integral, and divergent-ray descriptions of tomographic data. The Radon transform. Reconstruction from ideal data: filtered back-project, back-project filter, Fourier, and inverse Radon-transform methods. Reconstruction from ideal data: filtered back-project, back-project filter, Fourier, and inverse Radon-transform methods. Reconstruction from blurred and noisy data: confidence-weighting, minimum-divergence deblurring, and estimation-based methods. Techniques for treatment of mission data, attenuation, and accidentals. Application to positron-emission, single-photon emission, x-ray, and magnetic-resonance tomography and to high resolution radar-imaging. Computer architectures for producing tomographic imagery. Prerequisite: ESE 520.
E35 - ESE	587	Ultrasonic Imaging	3
		Propagation of ultrasound in inhomogeneous media, near-field and far-field descriptions, refraction and diffraction, dispersive media models, acoustic wave equation formulations and solutions. Basic elements of transducer, pulser, and receiver design. The use of linear versus logarithmic amplifiers. Time-gain compensation, scan conversion, and image generation in single-transducer systems. Phased-array imaging systems. Synthetic-aperture acquisition, synthetic-focus image generation. Ellipsoidal backprojection using the complete dataset. Design of restoration filters to compensate for diffraction effects of the transducer. Estimation of media properties from images. Prerequisite: ESE 351.
E35 - ESE	588	Quantitative Image Processing	3
		Introduction to the modeling processing and display of images. Two-dimensional linear systems and linear processing of images. Two-dimensional transform methods. Image acquisition and display technology. Psychophysical aspects of vision. Case studies in image processing (examples: tomography, radiology, ultrasonic imaging). Special algorithms for image processing (examples: boundary detection, segmentation, compression, interactive processing and display). Prerequisites: CS 136G, ESE 326, ESE 482.
E35 - ESE	589	Biological Imaging Technology	3
		This class will develop a fundamental understanding of the physics and mathematical methods that underlie biological imaging and critically examine case studies of seminal biological imaging technology literature. The physics section will examine how electromagnetic and acoustic waves interact with tissues and cells, how waves can be used to image the biological structure and function, image formation methods and diffraction limited imaging. The math section will examine image decomposition using basis functions (e.g. fourier transforms), synthesis of measurement data, image analysis for feature extraction, reduction of multi-dimensional imaging datasets, multivariate regression, and statistical image analysis. Original literature on electron, confocal and two photon microscopy, ultrasound, computed tomography, functional and structural magnetic resonance imaging and other emerging imaging technology will be critiqued.
E45 - ESE	589	Biological Imaging Technology	3

E45 - ESE	591	Special Topics: Biomedical Topics I: Principles	3
		This course covers the principles of optical photon transport in biological tissue. Topics include a brief introduction to biomedical optics, single-scatterer theories, Monte Carlo modeling of photon transport, convolution for broad-beam responses, radiative transfer equation and diffusion theory, hybrid Monte Carlo method and diffusion theory, and sensing of optical properties and spectroscopy. Prerequisite: Differential equations
E35 - ESE	592	Special Topics: Biomedical Optics II: Imaging	3
		This course covers optical imaging technologies. Topics include ballistic imaging, optical coherence tomography, Mueller optical coherence tomography, diffuse optical tomography, photoacoustic tomography, and ultrasound-modulated optical tomography. Pre-reqs: Differential equations; Biomedical Optics I: Principles.
E35 - ESE	596	Seminar In Imaging Science And Engineering	1
		This seminar course consists of a series of tutorial lectures on Imaging Science and Engineering with emphasis on applications of imaging technology. Students are exposed to a variety of imaging applications that vary depending on the semester, but may include multispectral remote sensing, astronomical imaging, microscopic imaging, ultrasound imaging, and tomographic imaging. Guest lecturers come from several parts of the university. This course is required of all students in the Imaging Science and Engineering program; the only requirement is attendance. This course is graded Pass/Fail. Prerequisite: Admission to Imaging Science and Engineering Program.
E35 - ESE	597	Practicum In Imaging Science And Engineering	1
		This course provides students in the Imaging Science and Engineering program with opportunities to participate, early in their graduate studies, in projects involving image data. A list of IS&E faculty having potential projects of interest is provided. It is the student's responsibility to interview with such faculty in order to identify a project for themselves to be completed in one semester. A written report documenting the project goals, relevant literature, and results obtained is required at the end of the project. To receive credit for completing the practicum, the report must be accepted by the supervisor of the project and a committee of IS&E faculty. This course is graded Pass/Fail. Prerequisite: Admission to Imaging Science and Engineering Program. Same as E81 CSE 597 and E72 BME 507.
E35 - ESE	599	Masters Research	3

E35 - ESE	600	Doctoral Research	9

E35 - ESE	883	Masters Continuing Student Status	0

E35 - ESE	884	Doctoral Continuing Student Status	0

E35 - ESE	885	Masters Nonresident	0

E35 - ESE	886	Doctoral Nonresident	0

E35 - ESE	ELE1	Electrical And Systems Engineering Elective (freshmen)	3

E35 - ESE	ELE2	Electrical And Systems Engineering Elective (sophomore)	3

E35 - ESE	ELE3	Electrical And Systems Engineering Elective (junior)	3

E35 - ESE	ELE4	Electrical And Systems Engineering Elective (senior)	3

E35 - ESE	ELE5	Ese Elective (grad)	9

Department of Electrical and Systems Engineering, Washington University in St. Louis
One Brookings Drive, Box 1127, St. Louis, Missouri 63130
Office Location: Bryan 201, Phone: (314) 935-5565, Fax: (314) 935-7500