TY - GEN
T1 - Low cost parallel adaptive filter structures
AU - Chao, Cheng
AU - Parhi, Keshab K.
PY - 2005
Y1 - 2005
N2 - 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.
AB - 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.
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M3 - Conference contribution
AN - SCOPUS:33847655709
SN - 1424401313
SN - 9781424401314
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 354
EP - 358
BT - Conference Record of The Thirty-Ninth Asilomar Conference on Signals, Systems and Computers
T2 - 39th Asilomar Conference on Signals, Systems and Computers
Y2 - 28 October 2005 through 1 November 2005
ER -