The Recursive Least Squares (RLS) algorithm is an adaptive filtering technique that continuously updates the filter coefficients to minimize the weighted least squares of the error signal. This method allows for fast convergence and effective tracking of time-varying signals, making it ideal for applications like noise cancellation and beamforming. The RLS algorithm is particularly known for its computational efficiency and ability to adapt quickly to changes in the input signal or system dynamics.
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