Rapid frequency-domain adaptation of causal FIR filters

Stephen J. Elliott, Boaz Rafaely

Research output: Contribution to journalArticlepeer-review

8 Scopus citations


Normalizing the convergence coefficient of the block frequency-domain least mean square (LMS) algorithm in each frequency bin can improve the convergence rate, but in some applications can lead to a biased steady-state solution if the filter is constrained to be strictly causal. An algorithm is presented in which the spectral factors of the bin-normalized convergence coefficient are used before and after the causality constraint is applied in the adaptation algorithm, which converges rapidly to the optimal causal filter.

Original languageEnglish
Pages (from-to)337-339
Number of pages3
JournalIEEE Signal Processing Letters
Issue number12
StatePublished - 1 Dec 1997
Externally publishedYes


  • Adaptive filtering
  • Frequency-domain implementation
  • LMS algorithm
  • Spectral factorization


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