NDLI: A pipelined LMS adaptive filter architecture

Content Provider	IEEE Xplore Digital Library
Author	Shanbhag, N.R. Parhi, K.K.
Copyright Year	1991
Description	Author affiliation: Dept. of Electr. Eng., Minnesota Univ., Minneapolis, MN, USA (Shanbhag, N.R.; Parhi, K.K.)
Abstract	A fine-grain pipelined architecture for least mean-square (LMS) filtering is developed by employing a stochastic form of look-ahead. With the stochastic form of look-ahead one can look for acceptable convergence behavior rather than invariance with respect to the input-output mapping. This architecture offers a trade-off between a variable output latency and adaptation accuracy. Analytical expressions describing the convergence properties are provided. A comparison with previous work indicates that the novel architecture has the least increase in hardware requirements and at the same time has the highest convergence speed in seconds. Simulation results confirm the desired analytical expressions.
Starting Page	668
Ending Page	672
File Size	329585
Page Count	5
File Format	PDF
ISBN	0818624701
ISSN	10586393
DOI	10.1109/ACSSC.1991.186532
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-11-04
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Least squares approximation Adaptive filters Pipeline processing Signal processing algorithms Hardware Stochastic processes Convergence Algorithm design and analysis Concurrent computing Delay
Content Type	Text
Resource Type	Article
Subject	Signal Processing Computer Networks and Communications

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