Course
Adaptive Signal Processing
Adaptive signal processing catalog description.
Course information
New Mexico State University EE545 Adaptive Signal Processing (3 credits).
Prerequisites
EE545 Digital Signal Processing
Textbooks
- Adaptive Filter Theory 3rd Edition by Simon Haykin (ISBN 0-13-322760-X)
- DSP Software Toolkit by Phillip L. De Leon
Course Objectives
The objective of this course is to gain an understanding of Adaptive Signal Processing:
- Optimal filtering
- Adaptive filtering
- Applications of adaptive filtering
This objective is achieved through a graduate-level treatment of Adaptive Signal Processing including both theoretical and experimental work.
Course materials
New Mexico State University EE594 Adaptive Signal Processing lecture notes, homework and solutions, laboratories, and exams.
- Lecture Notes
- Homework and Solutions
- Old Exams
This page is intended as a stable home for official course documents and high-level information.
Emphasis
Optimal Estimation & Wiener Filtering
- Random processes and correlation matrices
- Mean-square error (MSE) criteria
- Linear minimum mean-square error (LMMSE) estimation
- Wiener filter theory and solutions
- Orthogonality principle
- Introduction to Kalman filtering
Skills
Adaptive Algorithms & Convergence
- Gradient-based adaptation and steepest descent
- Least Mean Squares (LMS) algorithm and variants
- Recursive Least Squares (RLS) algorithm
- Newton and quasi-Newton adaptive methods
- Convergence analysis and stability
- Performance metrics (misadjustment, excess MSE)
Preparation
Advanced Structures & Applications
- Adaptive filter structures (transversal, lattice)
- Frequency-domain adaptive filtering
- Adaptive system identification and modeling
- Adaptive noise and interference cancellation
- Beamforming and array processing
- Applications in communications, audio, and biomedical signals