Course Overview

• Class meets MWF at 11AM in Duncan Hall 1046.
• Instructor Office Hours: Thursdays 1:30-3:30, Abercrombie A204.

The course covers deterministic and stochastic discrete-time signal processing. One-dimensional and two-dimensional signals. Frequency- and time-domain techniques of filtering.
Prerequisites: Elec 301 and 331.

Course Outline

Fundamentals

• One- and N-dimensional signals and systems
• Sampling theorem
• Discrete-time Fourier transform, discrete Fourier transform, fast Fourier transform
• z-transforms: stability and minimum phase signals/systems

Linear filtering of signals

• Time domain: Difference equations and convolution
• Impulse invariance, bilinear transform
• FIR filter design
• 2D filter design

Statistical signal processing

• Stochastic signals: correlation functions and power density spectra
• Optimal filtering: Wiener filters
• Adaptive filters: LMS and array processing

Wavelets

• Discrete wavelet transforms
• Filterbanks
• Denoising

Recommended Text

Oppenheim, Schafer and Buck, Discrete-Time Signal Processing