This course focuses on problems algorithms and solutions for processing signals in an manner that is responsive to a changing environment Adaptive signal processing systems are developed which take advantage of the statistical properties of the received signals The course analyzes the performance of adaptive lters and considers the application of the theory to a variety of practical problems such as interference and echo cancellation signal and system identication and channel equalization The class is designed as an advanced statistical signal processing course in which students will build a strong foundation in approaching problems in such diverse areas as acoustic sonar radar geophysical biomedical and communications signal processing Understanding of the theoretical foundations of adaptive signal processing theory will be achieved through a combination of theoretical and computerbased homework assignments Detail.
This course covers lessons on Adaptive Filters,Stochastic Processes ,Correlation Structure,Convergence Analysis,LMS Algorithm,Vector Space Treatment to Random Variables,Gradient Adaptive Lattice, Recursive Least Squares,Systolic Implementation & Singular Value Decomposition.
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