EEL 4750 / EEE 5502: Foundations of Digital Signal Processing

Semester: Instructor: Time and location: M,W,F - in NEB 100 Dr. Harley Office Hours: M,W 10:30 AM - 11:30 AM or by appointment in NEB 441

Course Description

Welcome to EEL 4750 / EEE 5502: Foundations of Digital Signal Processing! The study of digital signal processing explores how we transform data into new representations to better understand, compress, and leverage it. We start the course with a rigorous review of tools from Signals and Systems: sampling, convolution, and Fourier representations. We then discuss advanced signal processing architectures: the short-time Fourier Transform, filter design, multi-rate processing, and filter banks. Finally, we explore applications of these architectures: linear prediction, adaptive filters, and power spectrum estimation.

In EEL 4705 / EEE 5502, we also start exploring in greater depth how engineers efficiently process data streams with digital signal processing. We will incorporate programming/coding assignments to focus on applications and build conceptual understandings from the theory. Overall, I hope the course will be fun for all of us.

Learning Objectives

At the completion of this course, you should be able to:

  1. Apply discrete-time systems to discrete-time signals
  2. Explain aliasing caused by under-sampling data
  3. Apply convolution and correlation to modify and locate signals
  4. Design a system with the Z-transform
  5. Create a Fast Fourier transform algorithm
  6. Analyze data with the short-time Fourier transform/spectrogram
  7. Design FIR & IIR filters for modifying time-domain signals
  8. Analyze data with a multi-channel filter bank
  9. Apply power spectrum estimation to improve time-frequency filtering and analysis

Prerequisites

EEL 3135 (Introduction to Signals and Systems) or equivalent

Grade Distribution:

Assignment EEL 4750EEE 5502
Homework (best 10 out of 12)20%20%
Code Problems (best 6 out of 7)20%20%
Midterm Exam I20%20%
Midterm Exam II20%20%
Midterm Exam III20%20%