The recently proposed Chen's LMS algorithm  costs only half multiplications that of the conventional direct-form LMS algorithm (DLMS). Despite of the merit, the algorithm lacked rigorous theoretical analysis. This work intends to characterize its properties and conditions for mean and mean-square convergences. Closed-form MSE are derived, which is slightly larger than that of DLMS algorithm. It is shown, under the condition that the LMS step size μ is very small and an extra compensation step size α is properly chosen, Chen's algorithm has comparable performance to that of the DLMS algorithm. For the algorithm to converge, a tighter bound for α than before is also derived. The derived properties and conditions are verified by simulations.
|Number of pages||4|
|Journal||ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings|
|State||Published - 1 Jan 1997|
|Event||Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP. Part 1 (of 5) - Munich, Ger|
Duration: 21 Apr 1997 → 24 Apr 1997