A justification for the improved performance of the multi-split LMS algorithm

This paper presents an analysis that justifies the improved performance of the multi-split LMS algorithm. It is shown that instead of reducing the eigenvalue ratio, the multi-split operation increases the diagonalization factor of the transformed input signal autocorrelation matrix, which assists the power normalized and time-varying step-size LMS algorithm used for updating the single parameters independently. Case studies and simulation results enable us to evaluate the improved performance of the multi-split LMS algorithm.