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- W2165220135 abstract "An analysis is presented of the stationary points of an adaptive algorithm that adjusts the perceptron weights. This algorithm is identical in form to the least-mean-square (LMS) algorithm, except that a hard limiter is incorporated at the output of the summer. In addition, a momentum term is included in the weight update; this modified algorithm is referred to as the momentum LMS (MLMS) algorithm. It is shown that the stationary points of the MLMS algorithm are not unique; they depend not only on the statistics of the input and the desired response, but also on the specific values used for the algorithm convergence parameters, the step size and convergence constant. >" @default.
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- W2165220135 date "2002-12-04" @default.
- W2165220135 modified "2023-09-25" @default.
- W2165220135 title "Analysis of a perceptron learning algorithm with momentum updating" @default.
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- W2165220135 doi "https://doi.org/10.1109/icassp.1990.115643" @default.
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