EE 451: Digital Signal Processing |
Required Textbook:
Proakis and Manolakis, Digital Signal Processing: Principles,
Algorithms, and Applications, 3rd Edition, Prentice Hall, 1996.
Recommended Software: MATLAB Student Version
Lectures: M W F 11am - 11:50am in Weir 132
Labs: One lab section, on Wednesday afternoon from 2:00-5:00pm in Workman 117
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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.
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Topics Covered:
- Review of signals and systems.
- Analysis of discrete-time systems.
- Difference equations and implementation of discrete-time systems.
- Z-transforms.
- Frequency analysis of signals and systems.
- Discrete-time Fourier transform.
- Fast Fourier transform algorithms.
- Structures of FIR and IIR filters.
- Quantization of filter coefficient and their effects.
- Design of FIR filters, i.e, linear phase using windows and frequency-sampling methods, optimum equiripple linear-phase FIR filters, differentiators, and hilbert transformers.
- Design of IIR filters from analog filters.
- Multirate digital signal processing.
- Spectral estimation.
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Grading:
Homeworks: 15%
3 Midterms: 20% each
Final: 20%
Class Participation: 5%
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Links:
Homeworks
MATLAB Tutorial
Sample MATLAB code
Quadrature Signals: Complex but not Complicated, by Richard Lyons
Solution of difference equations in the time domain, by Dr. William Rison
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