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  Graduate School-New Brunswick 2003-2005 Programs, Faculty, and Courses Electrical and Computer Engineering 332 Graduate Courses  

Graduate Courses

16:332:501(F) System Analysis (3) Fundamental system concepts, solution of linear differential and difference equations. Transform methods involving Fourier and Laplace transforms, double-sided Laplace transforms, Z-transforms, Hilbert transforms, convolution in time and frequency domain. Complex variables and application of Residue Theorem for transform inversion. Review of matrix algebra involving similarity transformations. Cayley-Hamilton theorem; state space concepts, controllability, observability, minimal realization.
16:332:503,504Electric Network Theory I,II (3,3) Network synthesis of driving point and transfer impedances using Foster, Bott-Duffin, Brune, and Darlington techniques; topological methods for analysis of active and passive networks; flow-graph techniques; state-space formulation of general networks; computer-aided network design. Prerequisite: 16:332:501.
16:332:505(S) Control System Theory I (3) Transform theory and transfer function concepts; Nyquist and Bode plots. Nyquist and Hurwitz criterion of stability and design techniques involving Hall and Nichols charts. Design of compensating networks via root locus technique. State-space formulation of control systems. Definition of stability in time domain for general systems; methods of finding stability constraints. Discrete systems; z-transforms; difference equations; stability criterion. Prerequisite: 16:332:501.
16:332:506(F) Control System Theory II (3) Review of state-space techniques; transfer function matrices; concepts of controllability, observability, and identifiability. Identification algorithms for multivariable systems; minimal realization of a system and its construction from experimental data. State-space theory of digital systems. Design of a three-mode controller via spectral factorization. Prerequisite: 16:332:505.
16:332:508(S) Sampled Data Control Systems (3) Methods of analysis and synthesis of discrete-time systems; various transformations and semigraphical techniques applied to both digital and digitally controlled continuous processes with deterministic and/or random signals. Prerequisite: 16:332:505.
16:332:510(S) Synthesis of Optimum Control Systems (3) Formulation of both deterministic and stochastic optimal control problems. Various performance indices; calculus of variations; derivation of Euler-Lagrange and Hamilton-Jacobi equations and their connection to two-point boundary value problems, linear regulator and the Riccati equations. Pontryagin`s maximum principle; its application to minimum time, minimum fuel, and bang-bang control. Numerical techniques for Hamiltonian minimization. Bellman dynamic programming; maximum principle and invariant imbedding. Prerequisites: 16:332:505, 506.
16:332:512(S) Nonlinear and Adaptive Control Theory (3) Nonlinear servo systems; general nonlinearities; describing function and other linearization methods; phase-plane analysis and Poincare theorems. Liapunov`s method of stability; Popov criterion; circle criterion for stability. Adaptive and learning systems; identification algorithms and observer theory; input adaptive, model-reference adaptive, and self-optimizing systems. Estimation and adaptive algorithms via stochastic approximation. Multivariable systems under uncertain environment. Prerequisite: 16:332:505.
16:332:514(S) Statistical Design of Automatic Control Systems (3) Response of linear and nonlinear systems to random inputs. Determination of statistical character of linear and nonlinear filter outputs. Correlation functions; performance indices for stochastic systems; design of optimal physically realizable transfer functions. Wiener-Hopf equations; formulation of the filtering and estimation problems; Wiener-Kalman filter. Instabilities of Kalman filter and appropriate modifications for stable mechanization. System identification and modeling in presence of measurement noise. Prerequisite: 16:332:505.
16:332:519Advanced Topics in Systems Engineering (3) Advanced study of various aspects of automatic control systems. Possible topics include identification, filtering, optimal and adaptive control, learning systems, digital and sampled data implementations, singular perturbation theory, large-scale systems, game theory, geometric control theory, and control of large flexible structures. Topics vary from year to year. Prerequisite: Permission of instructor.
16:332:521(F) Digital Signals and Filters (3) Sampling and quantization of analog signals; z-transforms; digital filter structures and hardware realizations; digital filter design methods; DFT and FFT methods and their application to fast convolution and spectrum estimation; introduction to discrete-time random signals. Corequisite: 16:332:501.
16:332:525(F) Optimum Signal Processing (3) Block processing and adaptive signal processing techniques for optimum filtering, linear prediction, signal modeling, and high-resolution spectral analysis. Lattice filters for linear prediction and Wiener filtering. Levinson and Schur algorithms and their split versions. Fast Cholesky factorizations. Periodogram and parametric spectrum estimation and superresolution array processing. LMS, RLS, and lattice adaptive filters and their applications. Adaptation algorithms for multilayer neural nets. Prerequisite: 16:332:521 or permission of instructor.
16:332:526(S) Robotic Systems Engineering (3) Introduction to robotics; robot kinematics and dynamics. Trajectory planning and control. Systems with force, touch, and vision sensors. Telemanipulation. Programming languages for industrial robots. Robotic simulation examples.
16:332:527(S) Digital Speech Processing (3) Acoustics of speech generation; perceptual criteria for digital representation of audio signals; signal processing methods for speech analysis; waveform coders; vocoders; linear prediction; differential coders (DPCM, delta modulation); speech synthesis; automatic speech recognition; voice-interactive information systems. Prerequisite: 16:332:521.
16:332:529(S) Image Coding and Processing (3) Visual information, image restoration, coding for compression and error control, motion compensation, advanced television. Prerequisites: 16:332:521, 16:642:550. Recommended: 16: 332:535.
16:332:533(S) Computational Methods for Signal Recovery (3) Linear shift varying systems; discrete constrained estimation techniques; applications in image restoration; image reconstruction; spectral estimation and channel equalization using decision feedback. Prerequisites: 16:332:521, 541.
16:332:535(F) Multiresolution Signal Processing Algorithms (3) Algebraic models and algorithms, sampling lattices, multiresolution transforms, filters, rate conversion, deconvolution and projection. Prerequisite: 16:332:521 or permission of instructor. Corequisite: 16:642:550.
16:332:539Advanced Topics in Digital Signal Processing (3) Emphasis on current research areas. Advanced treatment of such topics as digital filter design, digital filtering of random signals, discrete spectral analysis methods, and digital signal processor architectures. Prerequisite: Permission of instructor.
16:332:541(F) Stochastic Signals and Systems (3) Axioms of probability; conditional probability and independence; random variables and functions thereof; mathematical expectation; characteristic functions; conditional expectation; Gaussian random vectors; mean square estimation; convergence of a sequence of random variables; laws of large numbers and Central Limit Theorem; stochastic processes, stationarity, autocorrelation, and power spectral density; linear systems with stochastic inputs; linear estimation; independent increment, Markov, Wiener, and Poisson processes. Corequisite: 16:332:501.
16:332:542(S) Information Theory and Coding (3) Noiseless channels and channel capacity; entropy, mutual information, Kullback-Leibler distance, and other measures of information; typical sequences, asymptotic equipartition theorem; prefix codes, block codes, data compression, optimal codes, Huffman, Shannon-Fano-Elias, arithmetic coding; memoryless channel capacity, coding theorem and converse; Hamming, BCH, cyclic codes; Gaussian channels and capacity; coding for channels with input constraint; introduction to source coding with a fidelity criterion. Prerequisite: 16:332:541.
16:332:543(F) Communication Networks I (3) Introduction to telephony and integrated networks. Multiplexing schematics. Circuit and packet switching networks. Telephone switches and fast packet switches. Teletraffic characterization. Delay and blocking analysis. Queuing network analysis.
16:332:544(S) Communication Networks II (3) Network and protocol architectures. Layered-connection management, including network design, path dimensioning, dynamic routing, flow control, and random-access algorithms. Protocols for error control, signaling, addressing, fault management, and security control. Prerequisite: 16:332:543.
16:332:545(S) Communication Theory (3) Orthonormal expansions, effect of additive noise in electrical communications, vector channels, waveform channels, matched filters, band width, and dimensionality. Optimum receiver structures, probability of error, bit and block signaling, introduction to coding techniques. Prerequisite: 16:332:541.
16:332:546(S) Wireless Communications Technologies (3) Propagation models and modulation techniques for wireless systems, receivers for optimum detection on wireless channels, effects of multiple access and intersymbol interference, channel estimation, TDMA and CDMA cellular systems, radio resource management, mobility models. Prerequisite: 16:332:545.
16:332:547(F) Digital Communications I (3) Functional characterization of digital signals and transmission facilities, band-limited and time-limited signals, modulation and demodulation techniques for digital signals, error probability, intersymbol interference and its effects, equalization and optimization of baseband binary and M-ary signaling schemes. Application to satellite and space communication systems emphasized. Prerequisite: 16:332:545.
16:332:548(S) Digital Communications II (3) Continuation of 16:332:547. Application of information-theoretic principles to communication system analysis and design. Source and channel-coding considerations, rudiments of rate-distortion theory. Probabilistic error-control coding impact on system performance. Introduction to various channel models of practical interest, spread spectrum communication fundamentals. Current practices in modern digital communication system design and operation. Prerequisite: 16:332:547. Corequisite: 16:332:542.
16:332:549(S) Detection and Estimation Theory (3) Statistical decision theory, hypothesis testing, detection of known signals and signals with unknown parameters in noise, receiver performance, and error probability; applications to radar and communications. Statistical estimation theory, performance measures and bounds, efficient estimators. Estimation of unknown signal parameters, optimum demodulation, applications. Linear estimation, Wiener filtering, Kalman filtering. Prerequisite: 16:332:541.
16:332:551(S) Fading Communication Channels (3) Characterization and modeling of fading and/or dispersive channels, analog and digital communication system performance, diversity reception, optimum demodulators for channel memory effects. Applications include troposcatter, HF, atmospheric scattering, and optical channels. Emphasis on analysis of space communication and optical communication system performance. Prerequisite: 16:332:548.
16:332:555(F) Microwave Circuits: Design and Engineering (3) Overview of modern microwave engineering, including transmission line, network analysis, integrated circuits, diodes, amplifier and oscillator design. Prerequisite: 16:332:580 or equivalent.
16:332:556(S) Microwave Systems (3) Microwave subsystems, including front-end and transmitter components, antennas, radar, terrestrial communications, and satellites. Prerequisite: 16:332:580 or equivalent.
16:332:559Advanced Topics in Communications Engineering (3) Topics such as source and channel coding, modern modulation techniques, telecommunication networks, and information processing. Prerequisite: Permission of instructor.
16:332:560(F) Computer Graphics (3) Computer-display systems, algorithms, and languages for interactive graphics. Vector, curve, and surface-generation algorithms. Hidden-line and hidden-surface elimination. Free-form curve and surface modeling. High-realism image rendering.
16:332:561(F) Machine Vision (3) Image processing and pattern recognition. Principles of image understanding. Image formation, boundary detection, region growing, texture, and characterization of shape. Shape from monocular cues, stereo, and motion. Representation and recognition of 3-D structure. Prerequisite: 16:332:501.
16:332:562(S) Visualization and Advanced Computer Graphics (3) Advanced visualization techniques, including volume represen-tation, volume rendering, ray tracing, composition, surface representation, advanced data structures. User interface design, parallel and object-oriented graphic techniques, advanced modeling techniques. Prerequisite: 16:332:560.
16:332:563(F) Computer Architecture I (3) Fundamentals of computer architecture using quantitative and qualitative principles. Instruction set design with examples and measurements of use, basic processor implementation: hardwired logic and microcode, pipelining; hazards and dynamic scheduling, vector processors, memory hierarchy; caching, main memory and virtual memory, input/output, and introduction to parallel processors; SIMD and MIMD organizations.
16:332:564(S) Computer Architecture II (3) Advanced hardware and software issues in mainstream computer architecture design and evaluation. Register architecture and design, instruction sequencing and fetching, cross-branch fetching, advanced software pipelining, acyclic scheduling, execution efficiency, predication analysis, speculative execution, memory access ordering, prefetch and preloading, cache efficiency, low-power architecture, and issues in multiprocessors. Prerequisite: 16:332:563.
16:332:565(F) Neurocomputer System Design (3) Principles of neural-based computers, data acquisition, hardware architectures for multilayer, tree, and competitive learning neural networks, applications in speech recognition, machine vision, target identification, and robotics. Prerequisite: 16:332:563.
16:332:566(S) Parallel and Distributed Computing (3) Introduction to parallel and distributed computing technologies, including systems, architectures, programming models, languages, and software tools. Parallelization and distribution models; parallel architectures; cluster and networked metacomputing systems; parallel/distributed programming; applications; and performance analysis. Prerequisites: 16:332:563 and 564.
16:332:567(F) Software Engineering (3) Overview of software development process. Formal techniques for requirements analysis, system specification, and system testing. Distributed systems, system security, and system reliability. Software models and metrics. Case studies.
16:332:568(S) Software Engineering of Web Applications (3) Program-development and software-design methodologies. Abstract data types, information hiding, program documentation. Program testing and reusability. Axiomatic and functional models. Case studies. Prerequisite: 16:332:567.
 
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