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一種新的細胞神經(jīng)網(wǎng)絡(luò)陰影檢測器的研究

汪海明,  郭仕德,  余道衡

汪海明, 郭仕德, 余道衡. 一種新的細胞神經(jīng)網(wǎng)絡(luò)陰影檢測器的研究[J]. 電子與信息學報, 2003, 25(11): 1499-1504.
引用本文: 汪海明, 郭仕德, 余道衡. 一種新的細胞神經(jīng)網(wǎng)絡(luò)陰影檢測器的研究[J]. 電子與信息學報, 2003, 25(11): 1499-1504.
Wang Haiming, Guo Shide, Yu Daoheng. A new kind of shadow detector based on cnn-ubn[J]. Journal of Electronics & Information Technology, 2003, 25(11): 1499-1504.
Citation: Wang Haiming, Guo Shide, Yu Daoheng. A new kind of shadow detector based on cnn-ubn[J]. Journal of Electronics & Information Technology, 2003, 25(11): 1499-1504.

一種新的細胞神經(jīng)網(wǎng)絡(luò)陰影檢測器的研究

A new kind of shadow detector based on cnn-ubn

  • 摘要: 該文深入研究了一種新的二維細胞自動機(CA),找到了幾種新的算法規(guī)則可以用來實現(xiàn)字符的粗化處理和陰影檢測,并且用這些規(guī)則設(shè)計了幾種新的細胞神經(jīng)網(wǎng)絡(luò),文中詳細介紹了這些算法規(guī)則的布爾代數(shù)表達式和細胞神經(jīng)網(wǎng)絡(luò)學習算法。仿真結(jié)果證明了這種新的細胞神經(jīng)網(wǎng)絡(luò)是簡單而有效的,同時也證明了可以用 CA規(guī)則來設(shè)計新的細胞神經(jīng)網(wǎng)絡(luò),為細胞神經(jīng)網(wǎng)絡(luò)的設(shè)計找到了一種新穎有效的方法。
    Abstract: In this paper, a new kind of two-dimensional Cellular Automata (CA) is studied. Several algorithmic rules are discovered that can be used to design new Cellular Neural Networks (CNN) which can implement shadow detector and overstriking for character recognition. Their Boolean expressions and learning algorithms are introduced detailedly. The results of computer simulation confirm that this new approach is simpler and more effective than that given in the literature. Furthermore, these results also confirm that new CNN can be designed with CA rules and find a novel method to design CNN.
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  • L.O. Chua, L. Yang, Cellular Neural Networks: Theory, IEEE Trans. on CAS, 1988, 35(10),1257-1272.[2]L.O. Chua, L. Yang, Cellular Neural Networks: Applications, IEEE Trans. on CAS, 1988, 35(10),1273-1290.[3]T. Kozek, T. Roska, A double time-scale CNN for solving two-dimensional Navier-Stokes equations, International Journal of Circuit Theory and Applications, 1996, 24(1), 49-55.[4]P.L. Venetianer, F. Werblin, T. Roska, Analogic CNN algorithms for some image compression and restoration tasks. IEEE Trans. on CAS-I, 1995, 42(5), 278-284.[5]C. Rekeczky, CNN architectures for constrained diffusion based locally adaptive image processing,International Journal of Circuit Theory and Applications 2002, 30(2/3): 287-312.[6]Jianye Zhao, Daoheng Yu, A new approach for ME multilevel image restoration based on CNN,International Journal of Circuit Theory and Applications, 1999, 27(3), 339-346.[7]Jianye Zhao, Haiming Wang, Daoheng Yu, A new approach for edge detection of noisy image based on CNN, International Journal of Circuit Theory and Applications, 2003, 31(2), 119-131.[8]S. Wolfman, Theory and Applications of Cellular Automata. Singapore, World Scientific Publishing, 1986 (Including all selected papers 1983-1986).[9]H. Masahiko, T. Aoki, H. Morimitsu, T. Higuchi, Implementation of reaction-diffusion cellular automata, IEEE Trans. on Circuits and Systems I: Fundamental Theory and Applications, 2002,49(1), 10-16.[10]P. Dasgupta, S. Chattopadhyay, P.P. Chaudhuri, I. Sengupta, Cellular automata-based recursive pseudoexhaustive test pattern generator. IEEE Trans. on Computers, 2001, 50(2), 177-185.[11]L.O. Chua, B.Shi, Exploiting Cellular Automata in the Design of Cellular Neural Networks for Binary Image Processing, ERL memo UCB/ERL M89/130, University of California, Berkeley,Nov. 15 , 1989.[12]T. Matsumoto, L. O. Chua, H. Suzuki, CNN cloning template: shadow detector, IEEE Trans. on CAS, 1990, 37(8), 1070-1073.[13]N.N. Aizenberg, I. N. Aizenberg, CNN-like networks based on multi-valued and universal binary neurons: learning and application to image processing, Cellular Neural Networks and their Applications, 1994. CNNA-94. Proceedings of the Third IEEE International Workshop on, Rome,Italy, 1994, 153-158.
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出版歷程
  • 收稿日期:  2002-06-24
  • 修回日期:  2002-11-14
  • 刊出日期:  2003-11-19

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