Catalog Data:
EE 424. Introduction to Digital Signal Processing. (3-3) Cr. 4. S. Prereq: 321. Fourier transform of discrete-time signals. Discrete Fourier transform and its application to convolution, correlation, and spectral estimation. Design of IIR and FIR filters. Realization of discrete-time systems. Fast Fourier algorithms and computational complexity. Quantization effects in digital signal processing. Simulation and real-time laboratory experiments illustrating DSP principles and applications.
Textbook:
J. G. Praxes and D. G. Manolakis, Introduction to Digital Signal Processing, Macmillan, 1988.
Coordinator: J. P. Basart, Professor
Goals:
This course is designed to introduce students to both theoretical and practical aspects of digital signal processing.
Prerequisites by Topic:
1. Linear system theory
2. Fourier transform theory
Topics:
1. Discrete-time signals and systems
2. Z-transform and analysis of discrete-time systems
3. Fourier transform and system frequency response
4. Discrete Fourier Transform - Application to convolution, correlation, and spectral estimation
5. Design of IIR and FIR filters
6. Realization of discrete-time systems
7. Fast Fourier Transform (FFT) algorithms and computational complexity
8. Quantization effects in digital signal processing
Computer Usage: Used in the laboratory experiments
Laboratory:
Several simulated and real-time experiments designed to consolidate the concepts learned during lectures will be performed. The experiments are based on i) Texas Instruments' TMS320C25 Software Development System, ii) Monarch DSP software, and iii) Atlanta Signal Processors' Digital Filter Design Package.
Estimated Content:
Engineering Topics: 2.5 credits
Design Experience:
Design of FIR and IIR filters using pole-zero placement. Design of IIR filters using bilinear transformation. Design of FIR filters using Frequency Sampling, Windowing, and Equiripple design techniques. Design and implementation of filters using the Digital Filter Design Package.