Adaptive Signal Processing
ND
Bibliographic details
Additional authors
STEARNS SAMUEL D
Summary
Summary by Topic Introduction to Adaptive Processing: Basics of adaptive systems and their significance in real‑time signal handling. Adaptive Linear Combiners: Formulation of the adaptive filter problem, objective functions, and system modeling. LMS Algorithm & Variants: Derivation, convergence criteria, stability issues, and performance in various scenarios. Advanced Adaptation Techniques: Includes normalized LMS, RLS (recursive least squares), and alternative gradient methods. Noise Cancellation and Beamforming: Real-world applications like echo cancellation and spatial filtering using adaptive arrays. Adaptive Inverse Control: Use in systems that compensate dynamic plant behavior via an adaptive model. Convergence Behavior & Performance Curves: Analysis tools such as learning curves, steady-state error, and sensitivity to eigenvalue spreads.