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Volume 18 Issue 1
Jan.  1996
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Yang Tao. SMOOTHING ALGORITHMS FOR BINARY IMAGE USING CELLULAR NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1996, 18(1): 7-14.
Citation: Yang Tao. SMOOTHING ALGORITHMS FOR BINARY IMAGE USING CELLULAR NEURAL NETWORKS[J]. Journal of Electronics & Information Technology, 1996, 18(1): 7-14.

SMOOTHING ALGORITHMS FOR BINARY IMAGE USING CELLULAR NEURAL NETWORKS

  • Received Date: 1994-02-01
  • Rev Recd Date: 1994-06-22
  • Publish Date: 1996-01-19
  • 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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  • Chua L O, Yang L. IEEE Trans. on CAS, 1988, CAS-35(10): 1257-1272.[2]Chua L O, Yang L. IEEE Trans. on CAS, 1988, CAS-35(10): 1273-1290.[3]Proceedings of the First IEEE International Workshop on Cellular Neural Networks and Their Ap-plications. Budapest: 1990.[4]Proceeding of the Second IEEE International Workshop on Cellular Neural Networks and Their Applications. Munich: 1992.[5]Special Issue on Cellular Neural Networks. Int. J Circuit Theory and Appl., 1992, 20(8).[6]Special Issue on Cellular Neural Networks: Theory. IEEE Trans. on CAS, 1993, CAS-I, 40(3).[7]Special Issue on Cellular Neural networks: Applications. IEEE Trans. on CAS, 1993, CAS-II, 40(3).[8][8][9]Fu K S, et al. Robotics: Control, Sensing, Vision and Intelligence. New York, North-Holland: 1985.[10]Yager R R, Zadeh L A. An Introduction to Fuzzy Logic Applications in Intelligent Systems, Boston: Kluwer Academic Publishers, 1992, 1-25.
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