ECE 510 Introduction to Signal Processing

3 Credit Hours

This course is the introductory graduate-level course in digital signal processing. It develops essential tools required for a broad range of disciplines (e.g. communications, geophysics, medical image processing, etc.). and provides background for graduate-level courses in communications and advanced signal processing. The course topics include properties and implementation of discrete-time signals and systems, analysis techniques using Z-Transform, Discrete-Time Fourier Transform, and Discrete Fourier Transform, sampling and reconstruction of signals, efficient computation methods using Fast Fourier Transform, and digital filter design.

Prerequisite

ECE 301, MATLAB experience.

Course Objectives

To provide students with understanding of discrete-time signals and systems and to develop digital signal processing design and analysis skills.

Course Requirements

Homework 15%, broken down as: Matlab/Problems 9% (drop the two lowest scores)
WebWork 6% (drop the two lowest scores)
Peer grading 5% (drop the two lowest scores; can opt out – see below)
Matlab Project(s) 15% (two group projects)
Midterm (in-class) 27%
Final exam 38%

+/- grading system will be used.
Credit will not be given for both ECE 510 and ECE 410 or 421.

Textbook

J. G. Proakis, D. G. Manolakis, “Digital Signal Processing: Principles, Algorithms and Applications,” Pearson, Fourth or Fifth Edition. Optional Textbooks: (one of these is recommended to assist with Matlab assignments): J. G. Proakis, V. K. Ingle, “Student Manual for Digital Signal Processing with MATLAB,” Prentice Hall; Vinay K. Ingle, John G. Proakis, “Digital Signal Processing Using Matlab,” Cengage Learning. Additional resources will be provided.

Created: 4/15/2024