MSE analysis of the M-max NLMS adaptive algorithm

TitleMSE analysis of the M-max NLMS adaptive algorithm
Publication TypeConference Paper
Year of Publication1998
AuthorsAboulnasr, T., and K. Mayyas
Conference NameAcoustics, Speech and Signal Processing, 1998. Proceedings of the 1998 IEEE International Conference on
Pagination1669 -1672 vol.3
Date Publishedmay.
Keywordsadaptive filter, adaptive filters, complexity, computational complexity, convergence, error, i.i.d. signals, iteration, iterative methods, least mean squares methods, M-max NLMS adaptive algorithm, mean square analysis, MMNLMS adaptive algorithm, MSE analysis, numerical stability, stability, steady state performance, update

In this paper, we provide a mean square analysis of the M-max NLMS (MMNLMS) adaptive algorithm introduced in Aboulnasr and Mayyas (1996). The algorithm selects, at each iteration, a specified number of coefficients that provide the largest reduction in the error. It is shown that while the MMNLMS algorithm reduces the complexity of the adaptive filter, it maintains the closest performance to the full update NLMS filter for a given number of updates. The stability of the algorithm is shown to be guaranteed for the extreme case of only one update/iteration. Analysis of the MSE convergence and steady state performance for i.i.d. signals is also provided for that extreme case


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