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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/29405


    Title: A LEARNING-MODEL OF THE FEATURE-DETECTING CELLS FOR UNSUPERVISED PATTERN-CLASSIFICATION
    Authors: WANG,WJ;LEE,DL
    Contributors: 電機工程研究所
    Keywords: RECOGNITION
    Date: 1994
    Issue Date: 2010-06-29 20:23:56 (UTC+8)
    Publisher: 中央大學
    Abstract: A modified neural network unsupervised learning scheme by the feature-detecting cell is proposed. We improve the performance in learning categories by adding a modulation system and a competing system to the conventional feature-detecting cell model. With the aid of the modultion system and the competing system, the cluster prototype which is closet to the input pattern will win the competitions and a winner dominated learning will be controlled by the properly assigned bias values. The proposed model has the following features: it guarantees the corresponding feature-detecting cell of each input pattern to be formed regardless of the initial weights and the duplication (of the feature-detecting cells formation for each sampled input pattern) can be reduced.
    Relation: PATTERN RECOGNITION LETTERS
    Appears in Collections:[電機工程研究所] 期刊論文

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