Electrical Engineering Course Description

ECE 5101 (3 credits) Introduction to System Theory

Modeling and analysis of linear systems. Introduction to functions of a complex variable. Linear algebra with emphasis on matrices, linear transformations on a vector space, and matrix formulation of linear differential and difference equations. State variable analysis of linear systems. Transform methods using complex variable theory, and time-domain methods including numerical algorithms.

 

ECE 5121 (3 Credits) Instructor Consent Required Multivariable Digital and Robust Control Systems

Analysis and design of robust multivariable control systems incorporating a digital computer as the controlling element. Topics include: Mathematical models of discrete-time systems, Discretization of continuous-time systems, Measures of control system performance, Classical single input-single output design methods, Compensator design via discrete-equivalent and direct design methods, State variable design via discrete equivalent and pole placement methods, Linear quadratic regulator (LQR) control, H2 and H-infinity optimal control, numerical optimization and nonlinear control.

 

ECE 5201 (3 Credits) Electromagnetic Wave Propagation

Engineering application of Maxwell’s field theory to electromagnetic wave propagation in various media. Reflection, refraction, diffraction, dispersion, and attenuation. Propagation in sea water and in the ionosphere.

 

ECE 5211 (3 Credits) Semiconductor Devices and Models

Band theory, conduction in semiconductors, carrier statistics, deep levels, impurities with multiple charge states, heavy doping effects, non-uniform doping. Non-equilibrium processes, carrier scattering mechanisms, the continuity equation, avalanche multiplication, carrier generation, recombination, and lifetime. P-n junctions, non-abrupt junctions, various injection regimes, and device models. Metal semiconductor junctions, current transport mechanisms, and models. BJT, JFET, MESFET, and MOSFET, and device models.

 

ECE 5212 (3 Credits) Fundamentals of Opto-Electronic Devices

Absorption and emission mechanisms in direct and indirect semiconductors. Semiconductor optoelectronic devices such as light-emitting diodes, injection lasers, photocathodes, solar cells, and integrated optics.

 

ECE 5213 (4 Credits) MOS Device & VLSI Fundamentals

Physics of MOS capacitors and transistors, derivation of V-1 relation expressing sub-threshold, threshold, and saturation region behavior; short-channel effects in scaled-down transistors; scaling laws; VLSI fabrication technologies; design and layout gates and gate arrays; physics, device layout and design of semiconductor memories including static and dynamic RAMs. Laboratory emphasizes introduction to nonvolatile RAMs; computer aids in VLSI design; schematic capture, SPICE simulation, layout of custom IC’s, and VHDL.

 

ECE 5223 (3 Credits) Nanophotonics

Principles and applications of nanophotonics with focus on optical metamaterials, plasmonics, and photonic bandgap crystals. Topics covered include electric plasma, magnetic plasma, optical magnetism, negative index matematerials, localized and non-localized surface plasmon polaritons, photonic bandgap structures, superlens, optical cloaking, surface enhanced Raman spectroscopy, transformation optics, plasmonic sensors, plasmonic waveguides.

Prerequisite: ECE 3223 or consent of instructor

 

ECE 5225 (3 Credits) Instructor Consent Required Electron Device Design and Characterization

Recommended Preparation: ECE 4211 or equivalent course Design and evaluation of micro/nano electronic devices using state-of-the-art computer simulation tools, ex-perimental electrical characterization of semiconductor devices and overview of modern electronic devices such as high-performance MOSFETs, TFTs, solar cells, non-volatile memories, CCDs, thermoelectric power generators. The electronic device (such as nanometer scale field effect transistor) design project will involve use of Synopsys tools to simulate the fabrication process, device simulation and performance evaluation. Components: Laboratory, Lecture

 

ECE 5231 (3 Credits) Instructor Consent Required Fund of Photonics

Principles of optics including rays, waves, beams, electromagnetics, polarization and statistics. Basic postulates, simple optical components, graded index and matrix optics, monochromatic waves, interference, polychromatic light, Gaussian beams and propagation, diffraction, Fourier transforms, holography, dispersion and pulse propagation, polarizing devices and applications. Concepts of coherence and partial coherence as applied to various light sources in optical experiments and systems.

 

ECE 5232 (3 Credits) Optoelectronic Devices

Optoelectronic devices as applied to fiber optic communications, optical switching and interconnects. Semiconductor laser devices, including dc, ac smallsignal, ac large signal, and noise with emphasis upon analytical models. Vertical cavity devices and technology. Semiconductor optical amplifiers, waveguide and vertical cavity modulators, photodetectors, optical switches, receivers and transmitters. Techniques for OE integration and the relevance of bipolar and field-effect devices for monolithic integration. Technologies for optoelectronic integration for telecom and datacom optical interconnect. WDM techniques for optical networks.

 

ECE 5233 (3 Credits) Optical Systems Engineering

Design and analysis of paraxial optical systems, including stable and unstable laser resonators, and the propagation of geometric beams, Gaussian beams, and plane waves through complex optical systems. Topics include ray optics; ray matrices; polarization of light; diffraction theory; the connection between geometrical optics and diffraction; and performance analysis.

 

ECE 5234 (3 Credits) Optical Waveguides

Propagation of electromagnetic waves in dielectric slab and fiber waveguides as described by geometrical ray optics and normal mode analysis. Integrated optic guides, step and graded index fiber guides. Single mode vs. multimode transmission, coupling, and other system considerations.

 

ECE 5301 (3 Credits) Instructor Consent Required Engineering Problems in the Hospital

Given in collaboration with staff from the University’s School of Medicine and from hospitals in Hartford. Aim is to familiarize the student with engineering problems in a modern hospital. Role of the small computer in the hospital; implanted pace-makers; heart catheterization. Students are expected to investigate and solve an engineering problem associated with clinical medicine as a semester project.

Course Equivalents: BME 5050

 

ECE 5510  Power System Analysis

Fundamentals of power system planning, operation, and management. Power generation and distribution. Modeling of AC generator, AC and DC motors, transformer and cable. Power flow solution. Modern power system monitoring/control, fault analysis, and transient stability analysis using computer tools. Use of power system simulation tools for power system planning and design.

Prerequisite: ECE 2001 – Electrical Circuits or equivalent

 

ECE 5512  Power Distribution

Principles of distribution system planning, automation and real-time operation with applications. Concepts of AC/DC Electricity. Three-phase power distribution as well as DC and Hybrid circuits. Load flow calculations, fault analysis, and reliability evaluation. Distributed power resources. Distribution system protection and reconfiguration. Smart distribution technologies. Efficient and resilient energy utilization.

Prerequisite: ECE 3231 – Introduction to Modern Power Systems or equivalent

 

ECE 5520  Advanced Power Electronics

Advanced converter and inverter topologies for high efficiency applications. Non-ideal component characteristics. Necessary components such as gate drive circuits and magnetic component design (that are not covered in introductory power electronics courses).

Prerequisite: ECE 3211 – Power Electronics or equivalent

 

ECE 5530  Modeling and Control of Electric Drives

Several topics related to modeling and control of electric drives. Fundamental equations related to inductance and flux variations in a rotating machine, leading to torque production. Reference frame theory and transformations for modeling purposes. Dynamic models of three-phase induction and permanent-magnet synchronous machines. Basic modeling of power electronic converters for electric drives, with focus on three-phase DC/AC inverters. Various control strategies with focus on vector control and different power electronic switching schemes in electric drives.

Prerequisite: ECE 3212 – Electric Machines and Drives or equivalent

ECE 5540  Electrical System Protection and Switchgear

Methods to sense voltage and current in medium and low voltage applications. Voltage sensing techniques include differential voltage amplifiers, shunt voltage measurement, and potential transformers. Current sensing techniques include current transformers, Rogowski coils, series voltage measurement, and Hall-effect sensors. Solid-state and mechanical relays and timing functions. Fuses and circuit breakers at medium voltage levels with focus on ratings, application-specific selection, and response time. Protection methods, e.g. differential protection, of transformers, generators, and cables with focus on distance relays and specialized devices.

Prerequisite: Instructor’s consent

Recommended preparation: ECE 3212 – Electric Machines and Drives or equivalent

ECE 5542  Asset Management and Condition Monitoring of Modern Power System

Principles of operation, monitoring and asset management of modern power systems. Operation, aging and failure modes as well as techniques for monitoring and diagnosis of power system assets. Power system plant basics and design; factors leading to electrical and thermal over stresses in power networks (fault currents and lightning and switching overvoltage transients) and corresponding mitigation solutions; aging mechanism and failure modes of key assets such as transformers, overhead lines or cabling networks, switchgear and gas insulated substations; modern techniques for diagnosis and condition monitoring such as partial discharge analysis; full life-cycle, reliability centric, predictive asset management strategy, statistics, economics, IT integration and data engineering. The development trend of condition monitoring for emerging applications.

Prerequisite: Instructor’s consent

Recommended preparation: ECE 3001 – EM Fields and Waves and ECE 3231 Introduction to Modern Power Systems or equivalent

 

ECE5544  Electrical Insulation System

Introduction to electrical insulation system for low and medium voltages. Gas discharge physics and dielectrics. Sulfur hexafluoride. Outdoor insulation. Dielectric breakdown in liquids and solids. Power capacitors and inductors. MV cables and accessories. Voltage transients in MV power systems. Thermal model for MV transformers (steady-state, transient, and hot-spot temperatures identification and verification). Insulation coordination design for MV transformers—load capacity and service lifting trade-off study based on electrical and thermal over-stress analysis. Insulation system for MV and LV rotating machines (form and random wound)—insulation system optimization for torque density and payload efficiency. Insulation system testing and qualification. Monitoring and diagnosis.

Prerequisite: Instructor’s consent

Recommended preparation: ECE 3001 – EM Fields and Waves and ECE 3231 Introduction to Modern Power Systems or equivalent

 

ECE 6095 (1 – 3 Credits) Special Topics in Electrical and Systems Engineering

Classroom and/or laboratory courses in special topics as announced in advance for each semester.

 

ECE 6099 (1 – 6 Credits) Instructor Consent Required Independent Study in Electrical Engineering

Individual exploration of special topics as arranged by the student with an instructor of his or her choice. Components: Independent Study

 

ECE 6101 (3 Credits) Linear Multivariable System Design

Observability and controllability. Application of canonic forms in system design. Methods of pole placement. Observer design. Noninteracting multivariable systems.

Prerequisites: ECE 5101

 

ECE 6102 (3 Credits) Instructor Consent Required Optimal and Model Predictive Control

Optimal Control, including optimization techniques for linear and nonlinear systems, calculus of variations, dynamic programming, the Pontryagin maximum principle, and computational methods. Linear Model Predictive Control, including process models and model prediction methods of state space description, transfer matrix representation, and neural network representation; and optimization methods without and with constraints. Nonlinear Model Predictive Control.

Prerequisite: ECE 5101 and ECE 6111

 

ECE 6103 (3 Credits) Nonlinear System Theory

Stability of time-varying nonlinear systems. Liapunov’s direct method. Describing functions. Popov’s stability criterion. Adaptive control.

Prerequisites: ECE 5101

 

ECE 6104 (3 Credits) Info Control & Games

Problems of static and dynamic optimization where more than one decision maker is involved, each having own payoff and access to different information. Review of elementary decision and control theory, non-cooperative games, cooperative games, bargaining models, differential games, team decision theory, Nash games, Stackelberg games (leader-follower problems). Introduction to large-scale systems and hierarchical control.

Prerequisite: ECE 5101 and ECE 6111

 

ECE 6105 (3 Credits) Man-Machine Systems Analysis

Role of the human as a decision and control element in a feedback loop. Mathematical models of human control characteristics and instrument monitoring behavior. Effects of human limitations upon overall task performance. Parallel discussion of measurement and experimental techniques. Validation of theoretical results by comparisons with existing human response data.

Prerequisite: ECE 5101 and ECE 6111

 

ECE 6106 (3 Credits) Instructor Consent Required Experimental Investigation of Control Systems

A study of experimental techniques and advanced design of control systems.

Prerequisite: ECE 6111 and ECE 6103

 

ECE 6107 (3 Credits) Stochastic Control

Methods of decision-making and control in a stochastic environment. Elements of utility theory. Principle of optimality and deterministic dynamic programming. Stochastic dynamic programming. Control of dynamic systems with imperfect state information. Certainty equivalence and the control’s dual effect. Sequential hypothesis testing. Passive and active stochastic adaptive control algorithms. Decentralized control methods.

Prerequisite: ECE 5101 or ECE 6111

 

ECE 6108 (3 Credits) Linear Programming and Network Flows

Computational methods for linear programming with special emphasis on sequential and parallel algorithms for Network Flow Problems. Standard and canonical forms of linear programming, revised Simplex methods, basis updates, decomposition methods, duality, shortest paths, minimal spanning trees, maximum flows, assignment problems, minimum cost network flows, and transportation problems.

Prerequisites: ECE 5101

 

ECE 6111 (3 Credits) Applied Probability and Stochastic Processes

Statistical methods for describing and analyzing random signals and noise. Random variables, conditioning and expectation. Stochastic processes, correlation, and stationarity. Response of linear systems to stochastic inputs.

 

ECE 6121 (3 Credits) Information Theory

Basic concepts: entropy, mutual information, transmission rate and channel capacity. Coding for noiseless and noisy transmission. Universal and robust codes. Information-theoretic aspects of multiple-access communication systems. Source encoding, rate distortion approach.

Prerequisite: ECE 6111

 

ECE 6122 (3 Credits) Digital Signal Processing

Discrete-time signals and systems. The z-transform. The Discrete Fourier Transform (DFT). Convolution and sectioned convolution of sequences. IIR and FIR digital filter design and realization. Computation of the DFT: The Fast Fourier Transform (FFT), algorithms. Decimation and interpolation. Parametric and nonparametric spectral estimation. Adaptive filtering. Finite word length effects.

 

ECE 6123 (3 Credits) Advanced Signal Processing

Wiener filter theory. Linear prediction. Adaptive linear filters: LMS and RLS algorithms, variants, lattice structures and extra-fast implementation. Convergence properties. High resolution spectral estimation. Hidden Markov models, Monte-Carlo methods for signal processing. Multiresolution decomposition and wavelets. Blind methods.

Prerequisites: ECE 6111 and ECE 6122 (RG332)

 

ECE 6124 (3 Credits) Advanced Signal Detection

Focus on discrete-time detection of signals in noise which is not necessarily Gaussian. Topics include: classical Neyman-Pearson and Bayes theory, efficacy and asymptotic relative efficiency; some canonical noise models; quantized detection; narrowband signal detection; distance measures and Chernoff bounds; sequential detection; robustness; non-parametric detection; continuous-time detection and the Karhunen-Loève expansion.

 

ECE 6125 (3 Credits) Digital Image Processing

Problems and applications in digital image processing, two-dimensional linear systems, shift invariance, 2-D Fourier transform analysis, matrix Theory, random images and fields, 2-D mean square estimation, optical imaging systems, image sampling and quantization, image transforms, DFT, FFT, image enhancement, two-dimensional spatial filtering, image restoration, image recognition, correlation, and statistical filters for image detection, nonlinear image processing, and feature extraction.

 

ECE 6126 (3 Credits) Optical Information Processing

Two-dimensional signal processing using optical techniques. Topics include: review of two-dimensional linear system theory; scalar diffraction theory, Fresnel and Fraunhofer diffraction; Fourier transforming and imaging properties of lenses; image formation; frequency analysis of optical imaging systems; modulation transfer function; two-dimensional spatial filtering; coherent optical information processing; frequency-domain spatial filter synthesis; holography, Fourier and nonlinear holograms.

 

ECE 6141 (3 Credits) Neural Networks for Classification and Optimization

This course provides students with an understanding of the mathematical underpinnings of classification techniques as applied to optimization and engineering decision-making, as well as their implementation and testing in software. Particular attention is paid to neural networks and related architectures. The topics include: Statistical Interference and Probabilty Density Estimation, Single and Multi-layer Perceptions, Radial Basis Functions, Unsupervised Learning, Preprocessing and Feature Extraction, Learning and Generalization, Decision Trees and Instance-based Classifiers, Graphical Models for Machine Learning, Neuro-Dynamic Programming.

 

ECE 6142 (3 Credits) Fuzzy and Neural Approaches to Engineering

Fuzzy sets, applications to fuzzy logic and fuzzy control, and concepts and methodologies for fuzzy optimization. Fundamental models of neural networks, learning rules, and basic recurrent networks for optimization. The integration of fuzzy systems with neural networks. Examples from engineering applications.

Prerequisites: ECE 5101

 

ECE 6143 (3 Credits) Pattern Recognition and Neural Networks

Review of probability and stochastic processes. Statistical pattern recognition. Nonlinear signal processing and feature extraction. Correlation filters. Metrics for pattern recognition. Baysian classifiers. Minimum probability of error processors. Supervised and unsupervised learning. Perception learning methods. Multilayer neural networks. Applications to security and encryption.

 

ECE 6151 (3 Credits) Communication Theory

Design and analysis of digital communication systems for noisy environments. Vector representation of continuous-time signals; the optimal receiver and matched filter. Elements of information theory. Quantization, companding, and delta-modulation. Performance and implementation of common coherent and non-coherent keying schemes. Fading; intersymbol interference; synchronization; the Viterbi algorithm; adaptive equalization. Elements of coding.

Prerequisite: ECE 6111

 

ECE 6152 (3 Credits) Wireless Communication

Introduces basic concepts in wireless communication and networks with emphasis on techniques used in the physical layer of current and future wireless communication systems. Covers channel modeling, modulation, spread spectrum techniques, multiuser communication theory, wireless network protocols, and current cellular and PCS systems. Special topics in equalization and array signal processing are included.

Prerequisite: ECE 6122 and ECE 6151

 

ECE 6161 (3 Credits) Modern Manufacturing System Engineering

Issues and methods in modern manufacturing systems. Integrated product and process development. Design for quality, on-line quality control and improvement, reliability during product development, and design for testability. Computer-aided production management, production planning and scheduling, and optimization-based planning and coordination of design and manufacturing activities. Targeted toward students, professional engineers, and managers who want to have an impact on the state-of-the-art and practice of manufacturing engineering, and to improve manufacturing productivity

 

ECE 6211 (3 Credits) Antenna Theory and Applications

Analysis and synthesis of antenna systems including electric- and magnetic-dipole, cylindrical, helical, reflector, lens, and traveling-wave antennas. Theory of arrays including patterns, self and mutual impedances.

 

ECE 6212 (3 Credits) Microwave Techniques

A theoretical analysis of microwave components, systems, and measuring techniques. Scattering matrix analysis is applied to microwave devices having two or more ports.

 

ECE 6221 (3 Credits) Transport in Semiconductors

Topics include theory of energy bands in crystals; carrier scattering; the Boltzman equation and its approximations; low field transport; high field effects; transport in heterojunctions; quantum effects; and Monte Carlo simulation.

Prerequisite: Physics 5401

 

ECE 6222 (3 Credits) Advanced Semiconductor Devices

Fundamental properties of heterostructures, strained-layer superlattices, NIPI structures, multiple quantum well, quantum wire, and quantum dot structures. Operation, modelling of the electrical characteristics, design, and applications of HBJT, HEMT, and resonant tunneling devices. Second-order effects in submicron MOSFETs and MESFETs.

 

ECE 6231 (3 Credits) Advanced Optoelectronics

Review of optoelectronic devices and integrated circuit (IC) technologies (analog and digital); logic gates; self-electro-optic devices (SEEDs), microlasers, Fabry-Perot (F-P) etalons and optoelectronic IC (OEICs); modulators: F-P modulators (absorptive and refractive), spatial light modulators (SLMs) and their applications; bistable devices; bistable laser amplifiers, resonant tunneling transistor lasers, and polarization bistability; optical interconnects; architectural issues and optical processors based on S-SEED, optical neural networks, and other devices.

Prerequisite: ECE 5212

 

ECE 6232 (3 Credits) Nonlinear Optical Devices

Wave propagation in nonlinear media, generation of harmonics in optical materials, optical parametric processes, stimulated emission and scattering processes. Device modeling and application of fiber and semiconductor lasers, optical amplifiers and modulators. Electro-optic, acousto-optic, and magneto-optic devices. Soliton generation and propagation.

Prerequisite: ECE 5231

 

ECE 6241 (3 Credits) Electronic Materials

Physical and electronic properties, and device applications of disordered materials including amorphous semiconductors, liquid crystals, bubble-memory magnetic materials. Applications of amorphous semiconductors including xerography and solar cells.

Prerequisite: MSE 5313

 

ECE 6242 (3 Credits) Instructor Consent Required VLSI Fabrication Principles

Semiconductor materials and processing, emphasizing compound semiconductors, optoelec-tronic materials, shallow devices, and fine-line structures. Semiconductor material properties; phase diagrams; crystal growth and doping; diffusion; epitaxy; ion implantation; oxide, metal, and silicide films; etching and cleaning; and lithographic processes.

 

ECE 6243 (3 Credits) Nanotechnology Nanoelectronic and optoelectronic devices: Quantum confinement in 1D, 2D and 3D (quantum wells, wires, and dots) structures; density of states and carrier density in low-dimensional structures; fabrication methodology for quantum wire transistors and lasers; single-electron transistors/tunneling devices; growth and characterization of nanostructured materials with grain sizes in the range of 10-50 nm. Organic monolayers: Langmuir-Blodgett monolayers, Self-Assembled monolayers, Multi-layer structures, technological applications of organic thin films.

 

ECE 6244 (3 Credits) Instructor Consent Required Nanotechnology – II (Laboratory Course)

Growth and characterization of carbon nanotubes using vapor phase nucleation; Growth of cladded quantum dots using liquid and/or vapor phase techniques; Characterization using AFM and TEM and Dynamic scattering techniques; Nano-device processing highlighting E-Beam lithography, and self-assembly techniques; Project work involving fabrication of devices including LEDs, FETs and memory, detectors and sensors using quantum dots and nanotubes/wires.

Components: Laboratory, Lecture

 

ECE 6247 (3 Credits) Dielectric and Magnetic Materials Science

The macroscopic and microscopic views of dielectric and magnetic materials. Theories of spontaneous polarization and magnetization. Applications of anisotropic materials. Non-linear dielectrics at radio and optical frequencies. Superconductivity and superconducting magnets.

 

ECE 6301 (3 Credits) Biomedical Instrumentation I

Origins of bioelectric signals; analysis and design of electrodes and low-noise preamplifiers used in their measurement. Statistical techniques applied to the detection and processing of biological signals in noise, including the treatment of nerve impulse sequences as stochastic point processes. Methods of identifying the dynamic properties of biosystems.

Course Equivalents: BME 6500

Prerequisite: ECE 6111

 

ECE 6302 (3 Credits) Biomedical Imaging

Fundamentals of detection, processing and display associated with imaging in medicine and biology. Topics include conventional and Fourier optics, optical and acoustic holography, optical and digital image enhancement, ultrasonography, thermography, isotope scans, and radiology. Laboratory demonstrations will include holography and optical image processing.

Course Equivalents: BME 6400

 

ECE 6303 (3 Credits) Advanced Ultrasonic Imaging Technique

Introduction to advanced techniques of ultrasonic image formation for biomedical applications. Introduction to acoustic wave propagation. A,B,C,M and Doppler ultrasonic imaging modes. Interaction of ultrasound with biological tissues. Acoustical holography. Ultrasonic transducer design and calibration. Transducer arrays. Ultrasound detection modes. Laboratory demonstrations will include Schlieren visualization of ultrasound fields and transducer calibration techniques.

Course Equivalents: BME 5329

Prerequisite: EE 6302 or BME 6400

 

ECE 6304 (3 Credits) Instructor Consent Required Biomedical Instrumentation Laboratory

Experimental investigation of electrodes, transducers, electronic circuits, and instrumentation systems used in biomedical research and in clinical medicine.

Components: Laboratory

Course Equivalents: BME 6510

 

ECE 6305 (3 Credits) Medical Imaging Systems

Medical imaging principles and systems of x-ray, ultrasound, optical tomography, magnetic resonance imaging, positron emission tomography. The students are required to have the courses of instrumentation, signal analysis using Fourier Transform and Laplace transform. Students are also required to have advanced mathematics on differential equations and matrix calculations.

Course Equivalents: BME 6420

 

ECE 6311 (3 Credits) Communication and Control in Physiological Systems

Processing, transmission, and storage of information in nerve systems. Mechanisms of neuro-sensory reception, coding and signal-to-noise ratio enhancement. Analysis of invertebrate and vertebrate visual systems. Neural spatio-temporal filters in feature extraction and pattern recognition. Analysis of control systems and regulators associated with vision: e.g., gaze control, accommodation, pupil area, and intra-ocular pressure.

Course Equivalents: BME 6120

 

ECE 6421 (3 Credits) Advanced VLSI Design

Advanced concepts of circuit design for digital VLSI components in state of the art MOS technologies. Emphasis is on the circuit design, optimization, RTL design, synthesis, and layout of either very high speed, high density or low power circuits and systems for use in applications such as micro-processors, signal and multimedia processors, memory and periphery. Other topics include challenges facing digital circuit designers today and in the coming decade, such as the impact of scaling, deep submicron effects, interconnect, signal integrity, power distribution and consumption, and timing.

 

ECE 6422 (3 Credits) VLSI CAD Algorithms

Very large scale integrated circuit (VLSI) computer-aided design (CAD) tools, optimization techniques, and design automation algorithms, such as branch and bound, genetic algorithms, simulated annealing, and linear programing. VLSI physical design process including partitioning, floorplanning, placement, routing, compaction, and pin assignment.

 

ECE 6431 (3 Credits) Advanced Computer Networks and Distributed Processing Systems

Design and evaluation of distributed computer communication and processing systems. Case studies, development of suitable queuing and other models to describe and evaluate design problems such as capacity assignment, concentration and buffering, network topology design, routing, access techniques, and line control procedures.

Course Equivalents: CSE 5300 This course and CSE 330 may not both be taken for credit

 

ECE 6432 (3 ) Instructor Consent Required VLSI Design Verification and Testing

Introduction to the concepts and techniques of VLSI (very large scale integration) design verification and testing, details of test economy, fault modeling and simulation, defects, automatic test pattern generation (ATPG), design for testability (DFT), scan and boundary scan architectures, built-in self-test (BIST) and current-based testing. State-of-the-art tools are used for ATPG, DFT, test synthesis and power analysis and management.

 

ECE 6433 (3 Credits) Stochastic Models for the Analysis of Computer Systems and Communication Networks

Continuous and discrete-time Markov chains and their applications in computer and communication network performance and reliability evaluation. Little’s theorem and applications; review of stochastic processes; simple Markovian queues; open, closed, and mixed product-form networks; computational algorithms for closed and mixed product form networks; flow-equivalence and aggregation; M/G/1 queue with vacations and applications to time-division and frequency-division multiplexing; reservations and polling; multi-access communication; reliability and performability models of computer systems.

Prerequisite: ECE 6111

 

ECE 6435 (3 Credits) Advanced Numerical Methods in Scientific Computation

Development, application and implementation of numerically stable, efficient and reliable algorithms for solving matrix equations that arise in modern systems engineering. Computation of matrix exponential, generalized inverse, matrix factorizations, recursive least squares, eigenvalues and eigenvectors, Lyapunov and Riccati equations.

Prerequisites: ECE 5101

 

ECE 6437 (3 Credits) Computational Methods for Optimization

Computational methods for optimization in static and dynamic problems. Ordinary function minimization, linear programming, gradient methods and conjugate direction search, nonlinear problems with constraints. Extension of search methods to optimization of dynamic systems, dynamic programming.

Prerequisites: ECE 5101

 

ECE 6439 (3 ) Estimation Theory & Comp Alg

Estimation of the state and parameters of noisy dynamic systems with application to communications and control. Bayesian estimation, maximum-likelihood and linear estimation. Computational algorithms for continuous and discrete processes, the Kalman filter, smoothing and prediction. Nonlinear estimation, multiple model estimation, and estimator Kalman, multiple model estimation, and estimator design for practical problems.

Prerequisite: ECE 5101 and ECE 6111