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ECE Courses by TIG

Course NumberCourse Title and Catalog Description


Digital Processing of Speech Signals

The application of digital signal processing to problems in speech communication. Part of this goal requires a laboratory project.


Data Compression and Modeling

Theory and algorithms of signal encoding and decoding for data compression. Applications in information systems, digital telephony, digital television, and multimedia Internet.


Methods of Pattern Recognition with Application to Voice

Theory and application of pattern recognition with a special application section for automatic speech recognition and related signal processing.


Advanced Signal Processing Theory

A lecture and seminar treatment of the latest developments in signal processing. Emphasis is placed on current literature and emerging research areas.


Introduction to Signal Processing

Introduction to discrete-time signal processing and linear systems. Sampling theorem. Filtering. Frequency response. Discrete Fourier Transform. Z Transform. Laboratory emphasizes computer-based signal processing.


Cryptography and Security

Algebraic and number theory approaches to cryptographic techniques, information security, secret key and public key encryption, signature schemes, hash functions, message authentication, and key distribution. Credit not allowed for both ECE 6280 and CS 6260.


Radar Imaging

An in depth study of digital signal processing methods for Synthetic Aperture Radar (SAR) image formation. Methods are also applicable to sonar.


DSP Software Systems Design

Specification, evaluation, and implementation of realtime DSP applications on embedded DSP-based environments.


Fundamentals of Radar Signal Processing

Signal modeling including radar cross section, multipath, and clutter. Properties of the ambiguity function and coded waveforms. Algorithms for doppler processing, detection, and radar imaging.


Adaptive Filtering

Basic theory of adaptive filter design and implementation. Steepest descent, LMS algorithm, nonlinear adaptive filters, and neural networks. Analysis of performance and applications.


Medical Imaging Systems

A study of the principles and design of medical imaging systems such as X-ray, ultrasound, nuclear medicine, and nuclear magnetic resonance. Cross-listed with BMED 6786.


Introduction to Probability and Statistics for ECE

Introduction to probability, random variables, distributions, estimation, confidence intervals, linear regression and other tools for describing and managing uncertainty in electrical and computer engineering.


Signal Detection and Estimation

Detection theory and estimation theory and their application to communications and statistical signal processing problems.


Medical Image Processing

Studying biomedical image analysis techniques including image enhancement, analysis, classification, and interpretation for medical decision-making through practicals and projects. Cross-listed with BMED6780.


Fundamentals of Digital Signal Processing

Introduction to Digital Signal Processing. Sampling Theorem,Discrete-time Fourier transform,power spectrum,discrete Fourier transform and the FFT algorithm,z-Transform, digital filter design and implementation.


Applications of Digital Signal Processing

Applications of DSP in speech, image processing, radar, pattern recognition, and adaptive filtering requiring working software implementations applied to the analysis of real signals.


Design Synthesis of Application-Specific Signal Processors

Fundamentals of theory and practice of DSP chip design in VHDL. Exposure to tools and environments for chip design, simulation, and verification.


DSP Hardware Systems Design

A study of theory and practice in the design and implementation of DSP algorithms on programmable processors, multiprocessors, and ASICs.


Spatial Array Processing

Introduce application areas where signals are sampled over space and time. Transfer knowledge of time-based techniques to spatial processing. Develop algorithms unique to spatial processing.


Digital Image Processing

An introduction to the fundamentals and the theory of multidimensional signal processing and digital image processing, including key applications in multimedia products and services including machine learning


Advanced Digital Signal Processing

An introduction to advanced signal processing methods that are used in a variety of application areas.


Statistical Machine Learning

An introduction to the theory of statistical learning and practical machine learning algorithms with applications in signal processing and data analysis.


Random Signals and Applications

Introduction to random signals and processes with emphasis on applications in ECE. Includes basic estimation theory, linear prediction, and statistical modeling.