Department of Electrical and Systems Engineering > Undergraduate Programs > Complete Course List

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Dept | # | Course Name :
[Course Description On]
| Credits |

ESE | 100 | Independent Study | 0 |

ESE | 101 | Introduction to Engineering Tools: MATLAB and SIMULINK | 1 |

Matlab and Simulink are important tools in quickly analyzing different designs in many engineering disciplines and are also perhaps the most used software in many engineering schools. Gain skills in the basics of the array-based language Matlab to write programs, including scripts and functions, to calculate and display variables and images. Learn the basics of Simulink to build and simulate models from standard blocks. Discover both Matlab and Simulink in an environment with supervised practice and hands-on experience. Practice problems are chosen from different engineering fields as well as from a few socio-economic fields so that students can see the software being exploited in real life applications. This is a pass/fail course. Prerequisite: Freshman standing | |||

ESE | 101 | Introduction to Engineering Tools: Matlab and Simulink | 1 |

Matlab and Simulink are important tools in quickly analyzing different designs in many engineering disciplines and are also perhaps the most used software in many engineering schools. Gain skills in the basics of the array-based language Matlab to write programs, including scripts and functions, to calculate and display variables and images. Learn the basics of Simulink to build and simulate models from standard blocks. Discover both Matlab and Simulink in an environment with supervised practice and hands-on experience. Practice problems are chosen from different engineering fields as well as from a few socio-economic fields so that students can see the software being exploited in real life applications. This is a pass/fail course. This course is open to all students, but preference will be given to freshmen students. | |||

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. Some of the technologies explored are used in a variety of applications including the iPod, Ultrasound Imaging, Computed Tomography, Radar, DC Motors and Credit Card Readers. Students work in groups of two in the newly renovated Bryan 316 laboratory. Each station is equipped with a Quad-Core computer and an integrated Data Acquisition system. Using this lab equipment, students design and build solutions to the exercises. The students also learn to program the computer in LabVIEW to control the Data Acquisition system. Also, throughout the semester, presentations are given by the EE faculty about their research. | |||

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. | |||

ESE | 151 | Introduction to Systems Science and Engineering | 2 |

Introduction to the methodology of systems engineering: mathematical modeling, deterministic and stochastic systems, optimization, utilization of scientific literature. Applications in engineering, environmental studies, sports, medicine, business, etc. Guest lecturers from various disciplines. Students are required to do mini research projects (in groups) and present their results. Grading is based on presentations and reports. (Not open to seniors or graduate students.) Prerequisite: Math 132, Physics 117A. | |||

ESE | 230 | Introduction to Electrical and 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. | |||

ESE | 231 | Electrical & Electronic Circuits Laboratory | 1 |

This course is limited to students who have taken JEE 230. Introduction to electronic meters, instruments, and power supplies to create and measure electrical current and voltage. Use of PSPICE and Multisim circuit simulation software to design and analyze electrical circuits. Construction, operation and measurement of electronic circuits comprising resistors, inductors, capacitors, transformers, audio speakers, DC motors, and basic inverting and non-inverting operational amplifier circuits. Weekly attendance at laboratory exercises is required. Prerequisite: JEE 230 and Math 217 or equivalent. | |||

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. | |||

ESE | 251 | Introduction to Systems Science and Engineering | 2 |

Introduction to the methodology of systems engineering: mathematical modeling, deterministic and stochastic systems, optimization, utilization of scientific literature. Applications in engineering, environmental studies, sports, medicine, business, etc. Guest lecturers from various disciplines. Students are required to do mini research projects (in groups) and present their results. Grading is based on presentations and reports. (Not open to seniors or graduate students.) Prerequisite: Math 132, Physics 117A. | |||

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. | |||

ESE | 297 | Introduction to ESE Undergraduate Research Projects | 2 |

This course is offered to students at all levels from all departments. The course is designed to give students some hands-on experience by implementing projects that use the lab PCs, the sbRIO robots from National Instruments, acoustic sensors, bio-medical sensors and 3D cameras. These projects are implemented in LabVIEW and Matlab and should prepare the students to work on topics that include the Robotic Sensing Undergraduate Research Projects in subsequent semesters. Note that under ESE 497 Undergraduate Research, students may select the Robotic Sensing Projects as well as other projects. Working in groups, students will implement algorithms that run on PCs and our wireless robotic platforms to track a moving audio source. Also, they will use an EEG system to implement a Brain Computer Interface (BCI) project and work with the new Kinect camera from Microsoft. Corequisite: CSE131 or equivalent | |||

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. Wednesdays are for exams and help sessions. Prerequisite: Math 217 or equivalent. | |||

ESE | 318 | Engineering Mathematics A | 3 |

Laplace transforms; matrix algebra; vector spaces; eigenvalues and eigenvectors; vector differential calculus and vector integral calculus in three dimensions. Prerequisites: Math 233 and Math 217 or their equivalents. | |||

ESE | 319 | Engineering Mathematics B | 3 |

Power series and Frobenius series solutions of differential equations; Legendre's equation; Bessel's equation; Fourier series and Fourier transforms; Sturm-Liouville theory; solutions of partial differential equations; wave and heat equations. Prerequisites: Math 233 and Math 217 or their equivalents. | |||

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. | |||

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. Pre-requisite: (1) 317 En Math or (2) Pre-requisite: ESE 318 En Math A and Co-requisite: ESE 319 En Math B. | |||

ESE | 331 | Electronics Laboratory | 3 |

Laboratory exercises provide students with a combination of hands-on experience in working with a variety of real instruments and in working in a simulated "virtual" laboratory setting. A sequence of lab experiments provide hands-on experience with grounding and shielding techniques, signal analysis, realistic operation amplifier (op amp) characterization, op amp based active filters characterization, MOSFET chopper/amplifier behavior, measurement of pulses propagating on a transmission line with various terminations, experience with both AM and FM modulation. Students will gain experience in working with: sampling oscilloscopes, various signal generators, frequency counters, digital multimeters, spectrum analyzers, and contemporary connection boards. The course concludes with a hands-on project to design and demonstrate an electronic component. Prerequisite: ESE 230. | |||

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. | |||

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. | |||

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. | |||

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 318 or 317. | |||

ESE | 352 | Introduction to Signals and Systems Lab | 1 |

Introduction to physical and computational aspects of signals and systems. Weekly laboratory experiments will complement the theoretical treatment in ESE 351, Signals and Systems. Experiments will illustrate fundamental concepts of linear systems, including state-space and input-output models, impulse response and convolution, transient and steady-state responses, time- and frequency-domain representations, system frequency response, and sampling, filtering and modulation. Matlab and/or LabView will be used for experiments and analysis of mechanical systems, electrical circuits, signals, and communication systems. Corequisite: ESE 351. | |||

ESE | 362 | Computer Architecture | 3 |

Study of interaction and design philosophy of hardware and software for digital computer systems. Processor architecture, Instruction Set Architecture, Assembly Language, Memory hierarchy design, I/O considerations. Comparison of computer architectures. Prerequisite: CSE 260M. | |||

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. --- In order to register for this course, please fill out the "ESE Research/Independent Study Registration form" found under the heading, "Course Schedules & Descriptions." | |||

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. | |||

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 317 or equivalent. ESE 403 is not a prerequisite for this course and it is possible to take this course without ESE 403. | |||

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. | |||

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. | |||

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. | |||

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. | |||

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. | |||

ESE | 427 | Financial Mathematics | 3 |

This course is a self-contained introduction to financial mathematics at the undergraduate level. Topics to be covered include pricing of the financial instruments such as options, forwards, futures and their derivatives along with basic hedging techniques and portfolio optimization strategies. The emphasis is put on using of discrete, mostly binary models. The general, continuous case including the concepts of Brownian motion, stochastic integral, and stochastic differential equations, is explained from intuitive and practical point of view. Among major results discussed are the Arbitrage Theorem and Black-Scholes differential equations and their solutions. Prerequisites: ESE 318 and 319 or ESE 317 and ESE 326 or the consent of the instructor. | |||

ESE | 428 | Probability | 3 |

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. | |||

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. | |||

ESE | 435 | Electrical Energy Laboratory | 3 |

Experimental studies of principles important in modern electrical energy systems. Topics include: AC power measurements, electric lighting, photovoltaic cells and arrays, batteries, DC-DC and DC-AC converters, and three-phase circuits. Each experiment requires analysis, simulation with MultiSim, and measurement via LabView and the Elvis II platform. Prerequisites: ESE 230 and 351 | |||

ESE | 437 | Sustainable Energy Systems | 3 |

We will survey the field of sustainable energy and explore contributions within electrical and systems engineering. Topics include introductory electric power systems, smart grids, and the roles of heat engines, photovoltaics, wind power, and energy storage, as well as analysis and optimization of energy systems. The course will consist of lectures, review and discussion of literature, and student projects. Prerequisite: ESE 317 or ESE 318 or ESE 319 and ESE 230 or ESE 351 or permission of instructor. | |||

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. | |||

ESE | 439 | Introduction to Quantum Communications | 3 |

This course covers the following topics: quantum optics, single-mode and two-mode quantum systems, nonlinear optics, and quantum systems theory. Specific topics include the following: Dirac notation quantum mechanics; harmonic oscillator quantization; number states, coherent states, and squeezed states; direct, homodyne, and heterodyne detection; linear propagation loss; phase insensitive and phase sensitive amplifiers; entanglement and teleportation; field quantization; quantum photodetection; phase-matched interactions; optical parametric amplifiers; generation of squeezed states, photon-twin beams, non-classical fourth-order interference, and polarization entanglement; optimum binary detection; quantum precision measurements; and quantum cryptography. Prerequisites: ESE 330, or PHY 421; Physics 217 or equivalent. | |||

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, 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 MEMS 431. | |||

ESE | 444 | Sensors and Actuators | 3 |

The course provides 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 5 conditions:(1) prerequisite of ESE 230 and corequisite of ESE 351;(2) prerequisites of ESE 230, ESE 317 and MEMS 255 (Mechanics II); (3) prerequisites of ESE 230, ESE 318 and MEMS 255 (Mechanics II); (4) prerequisites of ESE 151/251 and ESE 351; (5) permission of instructor. | |||

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. | |||

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 MEMS 431. | |||

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. | |||

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 441 or ChE 462 or equivalent. | |||

ESE | 455 | Quantitative Methods for Systems Biology | 3 |

Application of computational mathematical techniques to problems in contemporary biology. Systems of linear ordinary differential equations in reaction-diffusion systems, hidden Markov models applied to gene discovery in DNA sequence, ordinary differential equation and stochastic models applied to gene regulation networks, negative feedback in transcription and metabolic pathway regulation. Prerequisites: (1) Math 217, Differential Equations and (2) a programming course and familiarity with Matlab. | |||

ESE | 460 | Switching Theory | 3 |

ESE | 462 | Computer Systems Design | 3 |

Introduction to modern design practices, including the use of FPGA design methodologies. Students use a commercial CAE/CAD system for VHDL-based design and simulation while designing a selected computation system. Prerequisites: CSE 361S and 362M. | |||

ESE | 463 | Digital Integrated Circuit Design and Architecture | 3 |

This is a project oriented course on digital VLSI design. The course material will focus on bottom up design of digital integrated circuits, starting from CMOS transistors, CMOS inverters, combinational circuits and sequential logic designs. Important design aspect of digital integrated circuits such as propagation delay, noise margins and power dissipation will be covered in the class, as well as design challenges in submicron technology will be addressed. The students will design combinational and sequential circuits at various levels of abstraction using state-of-the-art CAD environment provided by Cadence Design Systems. The goal of the class is to design a microprocessor in 0.5 micron technology that can be fabricated by a semiconductor foundry. Prerequisites: CSE 260 and ESE 232 | |||

ESE | 465 | Digital Systems Laboratory | 3 |

ESE | 467 | Embedded Computing Systems | 3 |

Introduces the issues, challenges, and methods for designing embedded computing systems - systems designed to serve a particular application, which incorporate the use of digital processing devices. Examples of embedded systems include PDAs, cellular phones, appliances, game consoles, automobiles, and iPod. Emphasis is given to aspects of design that are distinct to embedded systems. The course examines hardware, software, and system-level design. Hardware topics include microcontrollers, digital signal processors, memory hierarchy, and I/O. Software issues include languages, run-time environments, and program analysis. System-level topics include real-time operating systems, scheduling, power management, and wireless sensor networks. Students will perform a course project on a real wireless sensor network testbed. Prerequisites: CSE 361S. | |||

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. | |||

ESE | 474 | Introduction to Wireless Sensor Networks | 3 |

This is an introductory course on wireless sensor networks for senior undergraduate students. The course will use a combination of lecturing and reading and discussion of research papers to help each student to understand the characteristics and operations of various wireless sensor networks. Topics covered include sensor network architecture, communication protocols on Medium Access Control and Routing, sensor network operation systems, sensor data aggregation and dissemination, localization and time synchronization, energy management, and target detection and tracking using acoustic sensor networks. The prerequisites include ESE 471 (communication theory and systems) | |||

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. | |||

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. | |||

ESE | 497 | Undergraduate Research | 3 |

Undergraduate research under the supervision of a faculty member. The scope and depth of the research must be approved by the faculty member prior to enrollment. A written final report and a Web page describing the research are required. | |||

ESE | 497B | Undergraduate Research | 3 |

Undergraduate research in the summer under the supervision of Dr. Arye Nehorai. Prerequisite: Undergraduate standing | |||

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. | |||

ESE | 499 | Capstone Design Project | 3 |

Term design project supervised by a faculty course adviser. The project must require use of the theory, techniques, engineering, and concepts of the student's major: electrical engineering or systems science & engineering. The project must have a client, typically either an engineer or supervisor from local industry or a professor or researcher in university laboratories. Namely a self-directed project is not allowed. 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 engineering methods, and terminating with an actual solution. Required documents are a written proposal, a final report, and a Web page on the project. An oral presentation of the project also is required. Prerequisite: ESE senior standing and instructor's consent. | |||

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. | |||

ESE | 499 | Capstone Project | 3 |

Term design project supervised by a faculty course adviser. The project must require use of the theory, techniques, engineering, and concepts of the student's major: electrical engineering or systems science & engineering. The project must have a client, typically either an engineer or supervisor from local industry or a professor or researcher in university laboratories. Namely a self-directed project is not allowed. 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 engineering methods, and terminating with an actual solution. Required documents are a written proposal, a final report, and a Web page on the project. An oral presentation of the project also is required. Prerequisite: ESE senior standing and instructor's consent. |