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Browsing by Author "Hsieh, BCY"

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    Non-saturated binary image learning and recognition using the ratio-memory cellular neural network (RMCNN)
    (2002)
    Wu, CY
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    Hsieh, CY
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    Chen, SH
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    Hsieh, BCY
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    Chen, CR
    dIn this paper, cellular neural network with ratio memory is proposed for non-saturated binary image processing. The Hebbien learning rule will be used to learn the weight of template A. The RMCNN system can recognize one non-saturated binary image and remove most of the noise added to the image pattern during the recognition period. The behavior of recognizing non-saturated binary images will be proved by mathematics equations. The effect will be simulated by Matlab software. With the method for non-saturated binary image processing, this theory can be easily implemented in hardware.