LMSNLMS
LMSNLMS refers to a class of adaptive filtering algorithms that combine ideas from the standard least-mean-squares (LMS) approach with normalized LMS (NLMS) concepts. The aim is to maintain the simplicity of LMS while achieving the robustness to input power variations that NLMS provides. In practice, LMSNLMS methods adjust the filter coefficients in response to the error between a desired signal and the filter output, using a step size or update rule that accounts for input signal power.
A representative implementation employs an NLMS-style normalization within the LMS framework, so the weight update uses
LMSNLMS methods are used in a range of adaptive filtering applications, including acoustic echo cancellation, channel
Key considerations include the choice of the base step size and the regularization parameter used in normalization,