Yu-Fan Chen

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We propose a fuzzy step size least-mean-square (LMS) algorithm, in which an appropriate step size is selected by a fuzzy inference system (FIS) to achieve faster convergence rate and lower steady-state fluctuation. An adaptive fuzzy sequential partial update scheme is developed to reduce system complexity without trading off bit-error rate (BER) and(More)
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