二值圖象平滑算法和細(xì)胞神經(jīng)網(wǎng)絡(luò)實(shí)現(xiàn)
SMOOTHING ALGORITHMS FOR BINARY IMAGE USING CELLULAR NEURAL NETWORKS
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摘要: 本文利用細(xì)胞神經(jīng)網(wǎng)絡(luò)(CNN)的基本處理單元一細(xì)胞的分段線性飽和輸出特性和相平面分析法實(shí)現(xiàn)了線性可分和線性不可分布爾函數(shù)。并利用這一原則實(shí)現(xiàn)了二值圖象的多種CNN平滑算法。Abstract: The piecewise linear saturation characteristics of cell in a cellular neural network(CNN) and phase plane analysis method are used to realize linear separable and nonseparable Boolean expressions. And the principle is also used to achieve some CNN smoothing algorithms for binary images.
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