• 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.
• 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
• Performance functions
• Gradient based methods
• Convergence analysis
• State-space description of signal model
• State estimation
Adaptive signal processing based on multiple input
• Signal and noise subspace
• MUSIC algorithms
Linear Algebra (F7-1) and Signal Analysis and Detection (SB7-1)
Project theme course (