Learning Characteristics of Transpose-Form LMS Adaptive Filters

Douglas L. Jones

Research output: Contribution to journalArticlepeer-review


Transpose-form filter structures have several advantages over direct-form structures for high-speed, parallel implementation of FIR filters. Transpose-form LMS adaptive filter architectures are often used in parallel implementations [1]-[5]; however, the behavior of these filters differs from the standard LMS algorithm and has not been adequately studied. This paper develops a method for determining the maximum convergence factor yielding convergence of the mean of the transpose-form LMS adaptive filter taps. The analysis reveals the great similarity of transpose-form LMS adaptive filters to delayed-update LMS adaptive filters, which have been much more fully characterized.

Original languageEnglish (US)
Pages (from-to)745-749
Number of pages5
JournalIEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing
Issue number10
StatePublished - Oct 1992

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering


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