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- W2327631598 abstract "A major, and yet unresolved, problem has been the choice of the step-size in some parameter tracking algorithms. This paper presents an adaptive setting method of step-size parameter for tracking time-varying parameters when normalized least mean square (NLMS) algorithm is used. The usual method suggested by Benveniste et al is to adjust the step-size so as to minimize the performance measure defined by the mean squares of prediction error. The weak point of this method is that the performance measure converges only on a local minimum.The main object of this paper is to give a solution for this problem. The solution obtained is that the performance measure converges on the global minimum through the minimization of another performance measure. As a result, the proposed algorithm becomes asymptotically optimal.Numerical examples indicate acceptable performance of the proposed method." @default.
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- W2327631598 date "1997-01-01" @default.
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- W2327631598 title "An Adaptive Setting Method of Step-Size Parameter in NLMS Algorithms" @default.
- W2327631598 doi "https://doi.org/10.5687/iscie.10.594" @default.
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