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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50970

Title: Competitive neural network scheme for learning vector quantization
Authors: Jung-Hua Wang
Chung-Yun Peng
Contributors: 國立臺灣海洋大學電機工程學系
Date: 1999-04
Issue Date: 2018-11-02T01:43:56Z
Publisher: IEE Electronics Letters
Abstract: Abstract: A novel self-development neural network scheme, which employs two resource counters to record node activity, is presented. The proposed network not only harmonises equi-error and equi-probable criteria, but it also avoids the stability-and-plasticity dilemma. Simulation results show that the new scheme displays superior performance (in terms of measured MSE, MAE, and training speed) over other neural network models.
Relation: 35(9) pp.725-726
URI: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/50970
Appears in Collections:[電機工程學系] 期刊論文

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