EE 378A – Statistical Signal Processing

Statistical models and algorithms for processing one- or multi-dimensional signals. Theory and mathematical tools.

Problems:

• Approximation

• Compression

• Denoising

• Linear inverse problems

• Dictionary learning

Tools:

• Function spaces, bases

• Wavelets

• Linear approximation and denoising

• Nonlinear approximation, denoising, compression

• Compressed sensing

• Bayesian inverse problems

• Deep learning approaches

Class Times and Locations

• Mon-Wed, 9:45-11:15am

• Hewlett 101