Digital Signal Processing

Course Description

Orthogonal expansions, z-transformation and its properties. Band limited signals and sampling theorem. Discrete-time systems. The design and realisation of digital filters. Non-recursive and recursive digital filtering. Multi-rate sampling. Auto-correlation and cross-correlation techniques. Matching filtering. Power frequency spectrum. Adaptive signal processing - random gradient method. The concept of Parametric Model and its applications for random signal power spectrum modern estimation, extraction and pattern recognition. Multi-channel signal processing by using Singular Value Decomposition (SVD). The introduction of Artificial Neural Networks.



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