Dr. Cranos Williams

Dr. Cranos Williams

Electrical and Computer Engineering

Phone: 919-513-1923
Fax: 919-515-5523
Instructor Website

ECE 513 Digital Signal Processing

3 Credit Hours

Digital processing of analog signals. Offline and real-time processing for parameter, waveshape and spectrum estimation. Digital filtering and applications in speech, sonar, radar, data processing and two-dimensional filtering and image processing.


ECE 421 Introduction to Signal Processing, B average in ECE and MA or Consent of Instructor

Course Objectives

The goals of this course are to provide graduate students with an understanding of discrete–time signals and the analytical tools to analyze and design digital signal processing systems. Upon completion of the course, the students will be able to:

  1. design FIR and IIR digital filters to meet arbitrary specifications
  2. develop algorithms to implement digital filters using Matlab or other high level languages such as C++,
  3. analyze the effects of the use of finite word sizes for the implementation of digital signal processing algorithms,
  4. develop and analyze algorithms for multirate digital signal processing, and
  5. be able to design and implement digital signal processing algorithms for applications related to digital communications, data acquisition,spectrum analysis, etc.

Course Topics

The following subjects are covered:

  1. Review of Fundamental DSP Concepts
    a. Discrete–Time Signals and Systems
    b. The Z–Transform and its Applications to the Analysis of LTI Systems
    c. Frequency Analysis of Signals
    d. Frequency Domain Analysis of LTI Systems
  2. Sampling and Reconstruction of Signals
  3. The Discrete–Time Fourier Transform: Its Properties and Applications
  4. Implementation of Discrete–Time Systems
  5. Analysis of Finite Word Length Effects
  6. Design of Digital Filters
  7. Multirate Digital Signal Processing

Course Requirements


Homework and computer assignments (25%)

Some homework assignments require writing Matlab routines for implementing digital signal processing algorithms.


2 exams during the semester (20% each for a total of 40%)

Final exam (35%)

Software Requirements:

  1. Matlab (The student version of Matlab with the Signal Processing Tool Box is the minimum acceptable level). Matlab can be accessed through the Virtual Computing Lab if you have a high speed internet connection.
  2. Word Processor to prepare home work assignments in a presentable manner.


John G. Proakis and Dimitris G. Monolakis, Digital Signal Processing: Principles, Algorithms and Applications, fourth edition, Pearson Prentice Hall, 2007,
ISBN 9780131873742.