Least Mean Squares (LMS) is an adaptive filter algorithm used to minimize the mean squares of the error signal between a desired output and the actual output of a system. It adjusts the filter coefficients dynamically based on incoming data, allowing for real-time adaptation to changing signals or environments. This method is crucial for applications such as noise cancellation, echo suppression, and system identification.
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