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A NEW NEURAL NETWORK BASED ALGORITHM FOR REAL TIME HARMONICS FILTERING Abstract

By Hsiung Cheng Lin, Cheng Siong Lee and Barry Adcock

Abstract

Conventional harmonics filtering approaches employ either passive or active systems or the combination of both. This paper proposes a neural network, based on an active filtering algorithm, which can be easily implemented in real time machine systems. Real data tests on the prototype model of the D.C. variable speed motor suggests that our proposed scheme is superior to the APLC's approach [8] in terms of faster training, converging, and simplicity in the hardware implementation. 1

Year: 2009
OAI identifier: oai:CiteSeerX.psu:10.1.1.135.2405
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