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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/2068

    Title: Character Recognition Based on the CMAC with An Annealed Chaotic Learning
    Contributors: Department of Computer Science and Information Engineerin National Chin-Yi Institute of Technology
    Keywords: CMAC;annealing;cooling schedulechaotic learning;pattern recognition
    Date: 2007
    Issue Date: 2009-10-13 15:20:14 (UTC+8)
    Publisher: Asia University
    Abstract: In this paper, a supervised parallel approach called CMAC (Cerebellar Model Arithmetic
    Computer) neural network with an Annealed Chaotic Learning (CMAC-ACL) scheme is proposed to
    characters recognition. The CMAC has many advantages in terms of speed of operation based on LMS training, its ability to realize arbitrary nonlinear mapping, and a fast practical hardware implementation.
    The CMAC can rapidly obtain output using a nonlinear mapping with look-up table memory to replace the complex learning process with mathematic functions. Additionally, an annealed chaotic learning scheme was embedded to escape from local minima and approach the global minimal solution. The proposed CMAC-ACL was applied to the character recognition in this paper. In the experimental results, the proposed CMAC-ACL has shown that it can clearly distinguish 94 characters in a keyboard
    with a size of 8?8 pixels, even though some noise pixels are added in a character.
    Relation: Asian Journal of Health and Information Sciences 2(1-4):66-78
    Appears in Collections:[Asian Journal of Health and Information Sciences] v.2 n.1-4

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