NEEC-6552 Digital Signal Processing II (CC 763)

Note: The following provides a suggested course description, objectives, and an outline. These may be modified pending discussion with the Faculty Chairs, proposing faculty, and other curriculum reviewers.

Course Description: An introduction to advanced signal processing methods that are used in a variety of application areas.

Course Objectives: To provide students with a background course in signal processing methods before they take courses in the individual application areas and to introduce them to signal processing.

Course Outline by Topical Areas:

Basic Signals and Systems

Review of 1-D signals

Review of random signals

Multi-D signals

Multirate Signal Processing

Interpolation and Decimation

Sample Rate Conversion

Oversampled Processing (A/D and D/A conversion)

Time-Frequency Representations

Filterbanks/Wavelets

Short-Time Fourier Transform

Wigner-Ville Decomposition

1-D and 2-D Transforms (DCT, DST, KLT)

Linear Prediction

Autoregressive Modelling and Least Squares

Modelling Random Signals

Prony's Method

Inverse Problems (Signal Reconstruction)

Underdetermined Least Squares

Pseudo-Inverse (SVD)

Min-Norm Solutions

Regularized Methods

Reconstruction from Projections

Iterative Methods

Projection onto Convex Sets

Expectation-Maximization

Simulated Annealing

Reconstruction from Nonuniform Sampling

1-D and Multi-D Sampling

Random Sampling

Optimal Quantization

Lloyd-Max Quantizers

Vector Quantization

 




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