Digital Signal Processing

Course Description

Introduction to the principles of signal processing, including discrete-time signals and systems, the z-transform, sampling of continuous-time signals, transform analysis of linear time-invariant systems, structures for discrete-time systems, the discrete fourier transform, computation of the discrete fourier transform, and filter design techniques. Computer Engineering 153, Electrical Engineering 153, and Electrical Engineering 250 are taught in conjunction. Students cannot receive credit for more than one of these courses. 

Prerequisite(s): Electrical Engineering 103. Enrollment restricted to School of Engineering and Division of Physical and Biological Sciences majors or permission of instructor.

Text

  • John G. Proakis and Dimitris G. Manolakis, “Digital Signal Proessing”, 4rd edition [Required]

Optional Helpful Texts

  • Proakis and Ingle, Digital Signal Processing with Matlab
  • Oppenhim and Schaeffer, Discrete-Time Signal Processing
  • Sanjit Mitra, “Digital Signal Processing:  A computer-based approach”
  • ="href=http://www.mathworks.com/access/helpdesk/help/techdoc/">Mathworks Online Documentation
  • Vetterli, Kovacevic, Goyal, “Foundations of Signal Processing”, 2013
    Preprint available online http://www.fourierandwavelets.org/more.php

Instructor: Professor Allie Fletcher

  • Office: 245A Engineering 2
  • Office Hours: Tuesday 2-3 PM and Thursday 11-12 AM
  • Email also for appointment

Grading

  • Homework, Quizzes  & Matlab 30%
  • Midterm 30%
  • Final 40%

 

Topics Covered

  • Overview of DSP
  • Discrete-time Signals
  • Fourier Transform & Frequency Domain Analysis
  • Discrete-time Systems: Difference Equaions & System Properties
  • The Z-transform & Inverse X-Transform
  • Sampling and Reconstruction of Continuous-Time Signals
  • Filter Design Techniques 
  • Discrete-Time Fourier Transform

Matlab Information

 

 

 

Instructors and Assistants