Variable weight mixed-norm LMS-LMF adaptive algorithm

TitleVariable weight mixed-norm LMS-LMF adaptive algorithm
Publication TypeConference Paper
Year of Publication1999
AuthorsAboulnasr, T., and A. Zerguine
Conference NameSignals, Systems, and Computers, 1999. Conference Record of the 33rd Asilomar Conference on
Pagination791 -794 vol.1
Keywordsadaptive filter, adaptive filters, adaptive signal processing, convergence, convergence of numerical methods, filtering theory, least mean fourth algorithm, least mean square algorithm, least mean squares methods, LMF cost function, LMS cost function, LMS-LMF adaptive algorithm, minimisation, objective function minimisation, step size bounds, time varying mixed-norm algorithm, time-varying filters, weighting factor

In this paper, we propose a new mixed norm LMS-LMF adaptive algorithm. The algorithm minimizes an objective function defined as a weighted sum of the least mean fourth (LMF) and least mean square (LMS) cost functions. The weighting factor is time varying and adapts itself so as to emphasize one cost function over the other based on proximity to the optimum. Improved convergence is illustrated by examples. Bounds on the step size to ensure mean convergence are also derived


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