Communications & Signal Processing Program
Overview
The convergence of information technology, telecommunications and broadcasting, is driving a rapid development of pervasive communication: systems and processes utilizing a high degree of communication among devices in a ubiquitous network infrastructure with wired and/or wireless components and adjuncts.
Communications and signal processing research is concerned with communications, signal processing, and networking and related engineering applications.
Syllabus
The communications and signal processing field of study contains the following subject matter:
- Communications: Communication theory, wireless communications, multiple antennas systems design, channel and source coding, and space-time coding.
- Signal Processing: Digital signal processing, machine vision, image processing, neural and soft computing, and intelligent machines.
- Computer Communication Networks: studies of data networks, flow control and routing in integrated networks, dynamic resource allocation in telecommunication networks, and high speed network real-time video multicasting.
Graduate Courses
EECS242 Information Theory (Credit Units: 3) Fundamental capabilities and limitations of information sources and information transmission systems. An analytical framework for modeling and evaluating communication systems. Prerequisite: EECS240A.
EECS243 Error Correcting Codes (3) S. Different techniques for error correcting codes and analyzing their performance. Linear block codes; cyclic codes; convolutional codes. Minimum distance; optimal decoding; Viterbi decoding; bit error probability. Coding gain; trellis coded modulation. Prerequisite: EECS240A.
EECS251A-B Detection, Estimation, and Demodulation Theory (3-3). Application of statistical design theory, state variables, random processes, and Ito calculus to deriving optimum rEECSiver structures for signal detection, parameter estimation, and analog demodulation. Prerequisite: EECS240A.
EECS241A Digital Communications I (Credit Units: 3) Concepts and applications of digital communication systems. Baseband digital transmission of binary, multi-mplitude, and multi-dimensional signals. Introduction to and performance analysis of different modulation schemes. Prerequisite: EECS240A.
EECS241B Digital Communications II (Credit Units: 3) Concepts and applications of equalization, multi-carrier modulation, spread spectrum and CDMA. Digital communications through fading memory channels. Prerequisite: EECS241A.
EECS248A Computer Communication Networks (3) F. Introduction to computer communication networks. Fundamental concepts of data communications, layered network architecture and network protocols. Integrated service networks and quality of service. The Internet Protocol and the Asynchronous Transfer Mode. Fundamental concepts of wireless networks and network security.
EECS248B Performance Analysis of Computer Communication Networks (3) W. Introduction to performance analysis of computer communication networks. Error correction codes and data link layer protocols. Queuing models for communication networks. Multi-access communication. Flow and congestion controls. Routing and admission control. Mathematical modeling and optimization of network performance and design. Prerequisite: EECS248A.
EECS250A Digital Signal Processing I (3). Fundamental principles of digital signal processing, sampling, decimation and interpolation, discrete Fourier transforms and FFT algorithms, transversal and recursive filters, discrete random processes, and finite-word effects in digital filters. Prerequisites: EECS152A, EECS260A, and EECS240A.
EECS203A Digital Image Processing (3) W. Pixel-level digital image representation and elementary operations; Fourier and other unitary transforms; compression, enhancement, filtering, and restoration; laboratory experience is provided. Prerequisite: EECS152A.
EECS203B Digital Image Understanding (3) S. Image and texture segmentation and symbolic representation; three-dimensional modeling; relational structures; three-dimensional object recognition; three-dimensional scene analysis and interpretation. Prerequisites: EECS101 and EECS203A.
EECS215 Design and Analysis of Algorithms (3) F. Computer algorithms from a practical standpoint. Algorithms for symbolic and numeric problems such as sorting, searching, graphs, network flow, and FFT considered. Analysis includes algorithm time and space complexity.
EECS240A Random Signals and Systems (3) F. Extensions of probability theory to families of random variables indexed on time. General properties of stochastic processes such as stationarity, ergodicity, stochastic continuity, differentiability, and integrability. Linear and nonlinear transformations, correlation, power spectrum, and linear filtering of stochastic processes. Linear mean-square estimation, the orthogonality principle, Wiener Kolmogoroff theory, filtering, and prediction. Wide-sense Markoff sequence, recursive filtering, and the Kalman filter. Prerequisite: EECS140.
Faculty
The following faculty members are affiliated with the communications and signal processing field of study:
E. Ayanoglu,
Rui J. P. de Figueiredo,
Glenn E. Healey,
Hamid Jafarkhani,
Scott Jordan,
Wei Kang (Kevin) Tsai
