Hardware description language (Verilog) design of processor systems for digital signal processing and data communication. Projects will be assigned in simulation and synthesis of dataflow and processor architectures targeting field programmable gate arrays (FPGA). Prerequisite: combinational and sequential digital design and finite state machines using hardware design tools.

Introduction to elemental and compound semiconductors; p-n junction, bipolar transistors, JFETs, MOSFETs; band diagrammatic techniques, scaling laws; device performance and device limitations.

Instruction set architectures, Register Transfer Level hardware description. Data-path design. Controller design. Caches and memory systems. Addressing. Microprogramming. Computer arithmetic. Survey of current computers and microprocessors. Projects will include Verilog/VHDL implementation of data-path components and testing them on FPGAs.

Introduction to elemental and compound semiconductors; p-n junction, bipolar transistors, JFETs, MOSFETs; band diagrammatic techniques, scaling laws; device performance and device limitations.

Topics covered are: various types of digital signal processing (DSP) techniques such as convolution, correlation, and filtering, as well as Finite Impulse Response (FIR) and Infinite Impulse Response (IIR) all pass and comb digital filters, the Discrete Fourier Transform, and the use of MATLAB as a tool for DSP software tasks. A term project will be assigned.

Introduction to Internet and TCP and IP protocols, telephone networks, Local Area Networks, packet switching, ATM, and other related topics.

An overview of the technologies, architectures and protocols used to build high-speed communication networks. Design and performance analysis techniques for computer communication networks. Topics will include: design and performance analysis of wired and wireless local networks, sensor networks, and Internet. Projects will include developing stochastic models, queuing analysis, and simulations.

Components of multimedia, basic multimedia tools, hardware and software, graphic design principles, human-computer interaction, multimedia project development and management.

Baseband pulse, digital, and passband communications systems; properties and bandwidth of signals and noise; detection of signals in noise; signal-to-noise ratio (SNR); distortionless transmission and intersymbol interference; pulse code modulation; amplitude, phase and frequency modulation and demodulation; simulation of communication systems.

Review of control concepts and application; state space representation of dynamical systems; controllability, observability; time invariant and time varying systems, design of full state feedback and output feedback systems; eigenstructure assignment; the linear quadratic regulator; Kalman filter; estimation and filtering; robust control via eigenstructure design, Kharitonov theorem, application examples.

Advanced study of electronic devices and their applications to linear, non-linear, and digital circuits; transistors, FET's, amplifiers, digital integrated circuits, and VLSI's; Software design emphasized. A term project will be assigned.

FIR and IIR digital filter design, finite word length effects, filter banks, multirate signal processing, spectral analysis (classical, modern, parametric and nonparametric techniques), adaptive filtering (Wiener filter theory) and speech production, analysis, and processing tools and speech coding. Computer experiments using MATLAB will be an integral part of the course.

Basics of artificial intelligence (AI) used in engineering applications. Propositional Calculus, Predicate Calculus, Automated reasoning; Prolog, Facts and Rules, Lists and Recursion, Backtracking, Built-in Predicates, Developing a Prolog program; Neural network, Basics of Neural Computing, Hopfield and BAM networks, Back Propagation Networks, applications.

This course provides an overview of concepts for the modern spectral analysis covering traditional approaches and modern estimation methods. It includes statistical estimation theory and performance measures. The properties, advantages and disadvantages of each estimator will be covered in detail using Cramer-Rao Lower Bound (CRLB) and sufficient statistics. These parametric estimators including Kalman filter will also be discussed, and some estimators will be implemented using computer programs (Matlab). Also we will exanimate some applications in spectral estimation, signal detection and beam forming.

Coherent and non-coherent detection of binary and M-ary signals in noise; waveform coding, linear block coding; convolutional, cyclic and turbo codes; error probability and bandwidth-efficiency plane in the design of digital communications systems; multipath and fading channels; simulation of communciation systems.

Introduction of the use of artificial intelligence techniques to develop intelligent systems. The course gives the student 1) an overview of what artificial intelligence is and its current state; 2) an overview of intelligent systems --what they are and their possible future role in society; 3) a practical and theoretical knowledge of expert systems, their development, implementation and maintenance and 4) an introduction to intelligent tutoring systems and to provide a perspective about the potential impact of these systems.

Introduction to elemental and compound semiconductors; p-n junction, bipolar transistors, JFETs, MOSFETs; band diagrammatic techniques, scaling laws; device performance and device limitations.

An introduction to a hierarchical design methodology of VLSI; study of basic logic elements and design methods in nMOS and CMOS; development of testable designs; the physics of MOS devices and fabrications processes; design rules and computation of circuit parameters from layout; system level design techniques; circuit structures with built-in self-test, design-for-test and self-checking features.

Nano challenges, quantum mechanics, nano materials, nanolithography, optics, carbon nanotubes, GaNa nanotechnology, MEMS and NEMS Architectures, Mathematical Model of MEMS and NEMS, Applications of Nanotechnology: Bio-Medical applications, Optical Devices, Sensors.

Special study in a particular aspect of Electrical Engineering under the direct supervision of a graduate faculty member.

Special study/internship in a particular aspect of Electrical Engineering.

Advanced course in the design and analysis of computer architecture. Topics will include instruction level parallelism, digital signal processors, network processors and multi-microprocessors. Projects will focus on the design, design analysis and FPGA implementations of computing systems.

This course will cover the design and analysis of packet switches such as Internet routers and Ethernet switches. Topics will include evolution of switches and routers, output scheduling, switch architectures, address lookup, packet classifiers and embedded firewalls.

Multimedia media and systems, multimedia applications, video-on-demand, video conferencing, interactive television, audio and frequency fundamentals, digital continuous media, compression and synchronization, digital media server and storage, multimedia documents and authoring, hypertext/hypermedia authoring, multimedia design.

Concept of optimality, calculus of variations, Euler-Lagrange equation, Pontryagin's minimum principle, Bellman's equation, Kalman filter, uncertainties in physical systems; structured and unstructured uncertainties; application of the Lyapunov method to robust control problems; robust optimal control; state space design for finite and infinite horizon problems; H-infinity design.

Nucleus system calls for multitasking real-time operating systems (RTOS); message passing protocols and processors; minimal nucleus architecture for embedded multiprocessor and dataflow RTOS. Prerequisite: C language programming

Spectral analysis of non-stationary signals, short-time Fourier transform, homomorphic filtering and filter bank, speech compression, and synthesis techniques. Weiner filtering for speech enhancement.

Temporal Logic: Intervals and points of Time, Temporal Reasoning, Applications in Verification and Validation of Digital systems; Fuzzy Logic: Definition of terms, Simple examples, Evaluation, Applications; Uncertain Knowledge and Reasoning: Uncertainty, Probabilistic Reasoning System; Learning: From Observation, From Neural and Belief Networks, Reinforced Learning; Communication and Perceiving; Application to Natural language processing: Perception, Robotics.

Signal detection and estimation in white and non-white noise, MAP estimation, applications in data and telecommunications. Wiener and Kalman-Bucy filters, linear and non-linear modulation.

Adaptive filter techniques such as Weiner filter, Linear Prediction, Least-Mean-Square, Recursive Least-Squares, Kalman Filtering algorithms. Introduction to the application of adaptive filters to communications, control, and speech processing.

State space modeling in the discrete time domain, recursive least squares estimation, persistently exciting input signals, direct and indirect adaptive prediction, model reference adaptive control, self tuning regulator, one-step-ahead control, adaptive pole placement, Kalman filter, Levinson predictor, stochastic approximation.

Introduction to photoptic and photon based devices and systems. Electro and magneto-optics, photon interaction with matter, light modulation, luminescence, and cathodoluminescience. Coherent and noncoherent sources, optical communication, and related topics.

Basic MOS device physics, single state amplifiers, frequency response, op amps, switched capacitor circuits, short-channel effects, amplifier design for wireless communication, low power static RAM architectures, layout and packaging.

This course provides an in-depth study of the design, engineering, and evaluation of modern parallel computers. Design issues covered include: naming, replication, synchronization, latency, overhead, and bandwidth. Other topics include scalable multiprocessors and interconnection network design.

Modeling of nonlinear systems, types of nonlinearity; Phase Plane Analysis, construction of phase portrait, limit cycle, saddle point; Existence and uniqueness of solutions, sensitivity; Lyapunov Stability, region of attraction, construction of Lyapunov functions; Perturbation Analysis variation of parameters, Method of averaging, Describing Functions, frequency domain analysis; Sliding Mode Control, sliding surface; Feedback Linearization, Lie algebra, state and output linearization, applications.

Modeling of nonlinear systems, types of nonlinearity; Phase Plane Analysis, construction of phase portrait, limit cycle, saddle point; Existence and uniqueness of solutions, sensitivity; Lyapunov Stability, region of attraction, construction of Lyapunov functions; Perturbation Analysis variation of parameters, Method of averaging, Describing Functions, frequency domain analysis; Sliding Mode Control, sliding surface; Feedback Linearization, Lie algebra, state and output linearization, applications.

2D digital filters, digital image edge detection and segmentation, feature extraction, deblurring, wavelet transforms, JPEG image compression, Fourier optics.

This course provides a comprehensive background in the principles and algorithms of VLSI physical design. The algorithms are presented in an intuitive manner so that the student can concentrate on the basic idea of the algorithms. The students are provided enough details to implement the algorithms.

Selected advanced topics in various major research areas under electrical and computer engineering.

Under the guidance of a faculty member, students will select a topic in electro-technology to be researched using at least five references. An extensive research paper must be submitted which will be reviewed by two faculty members. The project report must also be presented at an open seminar. Projects related to industrial applications are encouraged. For non-thesis students only.

Under the guidance of a faculty member, the student will conduct independent research on a selected topic in electrical and computer engineering. The research results will be presented in the form of a paper and an open seminar.

Under the guidance of a faculty member, the student will conduct independent research on a selected topic in electrical and computer engineering. The research results will be presented in the form of a paper and a research seminar.

Formulation of the thesis topic. Literature review and research of the proposed topic. Oral presentation and written submission of thesis proposal. For thesis students only.

Completion of the proposed research, and oral presentation of thesis work. Submission of the written thesis. For thesis students only.