Dr. Aly El-Osery ee

Last Updated: December 04 2017

EE 451: Digital Signal Processing

Required Textbook:

Proakis and Manolakis, Digital Signal Processing: Principles, Algorithms, and Applications, 4th Edition, Prentice Hall, 2007.


M W F 10am - 10:50am in Workman 113


on M W from 2:00-5:00pm in Workman 187

Course Description:

Signals play an important role in our everyday life. Digital signal processing (DSP) is a field that is concerned with the representation of such signals by sequences of numbers or symbols and the processing of these sequences. Due to the advances in integrated circuit technology, which offer economical implementations of very complex signal processing algorithms, DSP field has seen an explosive growth in the past three decades. This course will cover the basics in DSP. Applications of DSP will be demonstrated both during lectures and in lab. The course will cover various topics including: discrete-time signals and systems, z-transform, frequency analysis, discrete Fourier transform, and digital filters.

Topics Covered:

  1. Review of signals and systems.
  2. Analysis of discrete-time signals and systems.
  3. Frequency analysis of signals and systems.
  4. Discrete-time Fourier transform.
  5. Z-transforms.
  6. Fast Fourier transform algorithms.
  7. Structures of FIR and IIR filters.
  8. Quantization of filter coefficient and their effects.
  9. Design of FIR filters, i.e, linear phase  using windows and frequency-sampling methods, optimum equiripple linear-phase FIR filters, differentiators, and hilbert transformers.
  10. Design of IIR filters from analog filters.
  11. Multirate digital signal processing.
  12. Spectral estimation.


  • Homeworks: 20%
  • Quizzes: 15%
  • 2 Midterms: 20% each
  • Final: 20%
  • Class Participation: 5%


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