A new efficient LMS adaptive filtering algorithm

Sau Gee Chen*, Yung An Kao, Kwung Yee Tsai

*Corresponding author for this work

Research output: Contribution to journalJournal Article peer-review

13 Scopus citations


A new efficient LMS adaptive filtering algorithm is proposed. The algorithm has comparable performance to that of the direct-form LMS algorithm (DLMS), while costs N/2 - 1 fewer multiplications at the expense of N/2 + 5 more additions than the DLMS algorithm, where A is the number of filter taps. The new algorithm has one more parameter adaptation than the DLMS algorithm. Further, the algorithm was combined with sign LMS algorithm (SA), signed régresser algorithm (SRA) and zero forcing (ZFA) algorithm for more complexity reduction. Simulation results showed that the new combined algorithms converge as fast as the direct-form SA, SRA and ZFA algorithms, meanwhile still maintain comparable performances.

Original languageEnglish
Pages (from-to)372-378
Number of pages7
JournalIEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Issue number5
StatePublished - 1996
Externally publishedYes


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