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    Please use this identifier to cite or link to this item: http://ir.lib.ksu.edu.tw/handle/987654321/17321

    Title: Applicatiions of Cellular Neural Networks to Noise Cancelation in Gray Images Based on Adaptive Particel-swarm Optimization
    Authors: 蘇德仁
    Keywords: Cellular neural network;Adaptive particle-swarm optimization;Gray image noise cancelation;Templates
    Date: 2011-01
    Issue Date: 2012-09-06 14:06:51 (UTC+8)
    Abstract: This paper develops a novel method for designing templates for discretetime cellular neural networks (DTCNN) via an adaptive particle-swarm optimization (APSO) for gray image noise cancelation. Proper selection of the inertia weight for the APSO gives a balance between global and local searching. The research results show that a larger weight helps to increase the convergence speed while a smaller one benefits the convergence accuracy. This APSO-based method can automatically update template parameters of a discrete-time cellular neural network and optimize them to remove noise interference in polluted images. Finally, examples are given to illustrate the effectiveness of the proposed APSO-CNN methodology.
    Relation: Circuits Syst Signal Process
    Appears in Collections:[資訊工程系所] 期刊論文

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