Process / pipelineAdaptive signal processing

Adaptive LMS Filter

The Least Mean Squares (LMS) filter is an adaptive signal processing algorithm that continuously updates filter coefficients to minimize the squared error between the filter output and a desired signal. Introduced by Bernard Widrow and Marcian Hoff in 1960, the LMS algorithm is one of the most widely used adaptive filtering techniques due to its simplicity, low computational cost, and ability to track time-varying signals.

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Sources

  1. Widrow, B., & Hoff, M. E. (1960). Adaptive Switching Circuits. IRE Wescon Convention Record, 4, 96–104. link
  2. Haykin, S. (2002). Adaptive Filter Theory (4th ed.). Prentice Hall. link

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Referenced by

ScholarGateAdaptive LMS Filter (Least Mean Squares Adaptive Filter). Retrieved 2026-06-04 from https://scholargate.app/en/signal-processing/adaptive-lms-filter