Purpose:
• To enable the
students to apply theories and methods for design, analysis and realisation of
adaptive transversal and Lattice filters.
• To give the
students a general knowledge of adaptive IIR-filters, Kalman-filters
incl.
methods for adaptive processing of multiple input-signals.
Contents:
Adaptive MA-filters
• Performance
functions, the Wiener solution and gradient search
•
• LMS- and NLMS
algorithms incl. Convergence and stability criteria.
• Learning curves,
step size, and fault adjustment of weight factors
• RLS and fast RLS
algorithms
• Adaptive Lattice
MA-filters
Adaptive ARMA-filter
• Performance
functions
• Gradient based
methods
• Convergence
analysis
Kalman-filters
• State-space
description of signal model
• Innovation
• State estimation
Adaptive signal processing based on multiple input
• Signal and noise
subspace
• MUSIC algorithms
Prerequisites:
Linear Algebra (F7-1) and Signal Analysis and
Detection (SB7-1)
Duration:
2 ECTS
Category:
Project theme course (