Low cost parallel adaptive filter structures

Cheng Chao, Keshab K Parhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

In this paper, we present two parallel LMS adaptive filtering algorithms with low hardware. The proposed parallel algorithm 1 doesn't alter the input-output behavior and saves large amount of hardware cost of previous designs, especially when the parallelism level is high. For example, it saves 68.4% of the multiplications and 4.7% of the additions, of those of prior fast parallel adaptive filtering algorithms when parallelism level is 72 and the filter length N is large. The proposed parallel algorithm 2, while maintaining the same performance, can further save 5.56% to 12.5% of the multipliers and 8.54% to 24.9% of the additions when the level of parallelism varies from 3 to 72.

Original languageEnglish (US)
Title of host publicationConference Record of The Thirty-Ninth Asilomar Conference on Signals, Systems and Computers
Pages354-358
Number of pages5
StatePublished - Dec 1 2005
Event39th Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States
Duration: Oct 28 2005Nov 1 2005

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
Volume2005
ISSN (Print)1058-6393

Other

Other39th Asilomar Conference on Signals, Systems and Computers
CountryUnited States
CityPacific Grove, CA
Period10/28/0511/1/05

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