Proceedings PaperSchur RLS adaptive filtering using systolic arrays
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An interpretation of the tracking behavior of fast RLS adaptive filters is given. It is shown that the overall performance of an RLS adaptive filter is solely dependent on the forgetting function, which is involved in coefficient updating. Fast RLS adaptive filters restrict themselves to simple exponential or rectangular forgetting functions. Their tracking behavior is quite limited and sometimes even disappointing when compared to the much simpler LMS algorithm. These limitations can be circumvented with the advent of Schur RLS adaptive filters which allow the application of arbitrarily shaped forgetting functions in the coefficient updating process. Schur RLS adaptive filters are closely connected to the theory of discrete transmission lines. They are flexible in their possible configuration and share excellent structural and numerical properties, which make them highly attractive candidates for concurrent implementations. Systolic arrays of the Schur RLS adaptive filters are presented and their performance is demonstrated with a typical example.