A Pipelined LMS Adaptive Filter Architecture '
نویسندگان
چکیده
A f ine-grain pipelined architecture for least meaiisquare (LMS) filtering i s developed by employing a stochastic f o r m of look-ahead. T h e new architecture oflers a trade-off between a variable output latency and the adaptation accuracy. Analytical expressions describing the convergence properties are provided. A comparison with previous work indicates that the new architecture has the least increase i n hardware requiremen t s and at the same t i m e has the highest convergence speed i n seconds. Simulat ion results confirm the analytical expressions derived in this paper.
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تاریخ انتشار 2004