This course builds on the fourth semester course Signal Processing and covers adaptive systems in signal processing and control.
- Introduction with case studies
- MS algorithm and fundamental concepts in adaptive systems: optimality, convergence, stability, accuracy, robustness, tracking, data dependence, computational complexity, implementation and finite word-length effects
- Control applications: system identification, self-tuning control, model-reference adaptive control
- Signal Processing applications: channel equalization and adaptive detection, echo and noise cancellation, predictive coding and spectral estimation
- Selected special algorithms and systems: RLS, blind adaptation, lattice filters, nonlinear systems