ENCE 460: Digital Signal Processing

Instructor:

Liang Zhang, Assistant Professor

Prerequisites

ECE 220 and STAT 346, or permission of instructor.

Objectives

This course provides basic theory and important applications. Topics include probability concepts and axioms; stationarity and ergodicity; random variables and their functions; vectors; expectation and variance; conditional expectation; moment-generating and characteristic functions; random processes such as white noise and Gaussian; autocorrelation and power spectral density; linear filtering of random processes, and basic ideas of estimation and detection.

Location

EASC 2041

Time

Mon/Wed/Fri 12:00 pm -12:50 pm

ENCE 460 Syllabus

ENCE 460 Lecture Notes

Lectures Download Links
Lecture 0 Lecture 0 (pdf)
Lecture 1 Lecture 1 (pdf)
Lecture 2 Lecture 2 (pdf)
Lecture 3 Lecture 3 (pdf)
Lecture 4 Lecture 4 (pdf)
Lecture 5 Lecture 5 (pdf)
Lecture 6 Lecture 6 (pdf)
Lecture 7 Lecture 7 (pdf)
Lecture 8 Lecture 8 (pdf) Video part 1 (mp4) Video part 2 (mp4)
Lecture 9 Lecture 9 (pdf)
Annex (Generating RVs) Annex (pdf)
Lecture 10 Lecture 10 (pdf)
Lecture 11 Lecture 11 (pdf)
Lecture 12 Lecture 12 (pdf)
Lecture 13 Lecture 13 (pdf)
Lecture 14 Lecture 14 (pdf)
Lecture 15 Lecture 15 (pdf)
Lecture 16 Lecture 16 (pdf)
Formula Sheetpmf and pdf for exam

Projects

  1. Project 1

    Project     Solutions

  2. Project 2

    Project     Solutions

  3. Project 3

    Project     Solutions

Homework

Course Schedule

Week Lecture Topic
1 Lecture 0, Lecture 1 Course overview, Introduction to Digital Signal Processing, Discrete-Time Signals and Systems
2 Lecture 1, HW 1 Introduction to Digital Signal Processing, Discrete-Time Signals and Systems
3 Lecture 1A, HW 2 Review of probability: set theory, probability spaces
4 Lecture 2 The Fourier Transform
5 Lecture 3 Sampling theory
6 Lecture 4 The Z transform
7 midddle exam and Lecture 5 The system function and frequency response
8 Lecture 6 Transform analysis and properties
9 Lecture 7 System structures
10 Lecture 8 IIR filter design techniques
11 Lecture 8 FIR filter design techniques
12 Lecture 9 The Discrete Fourier Transform
13 Lecture 10 Properties of the DFT
14 Lecture 11 Fast Fourier Transforms
15 Lecture 12 Review Class - Last Class
16 Final Exam