DocumentCode :
1686960
Title :
Templates and algorithms for two-layer cellular neural networks
Author :
Yang, Zonghuang ; Nishio, Yoshifumi ; Ushida, Akio
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokushima Univ., Japan
Volume :
2
fYear :
2002
fDate :
6/24/1905 12:00:00 AM
Firstpage :
1946
Lastpage :
1951
Abstract :
Presents two-layer cellular neural networks for some image processing applications, in which two templates are introduced to couple between the two layers. Several simulations such as linear non-separable task, center point detection and skeletonizing, are executed with the two-layer CNN and their templates are given. All of them display that the two-layer CNNs behave more efficiently for image processing compared with single-layer CNNs. In addition, the stability of the two-layer CNN with symmetric templates and/or special coupling templates is also discussed based on the Lyapunov function technique. Its equilibrium points are found from the trajectories in a phase plane. These results agree with those from simulations
Keywords :
Lyapunov methods; cellular neural nets; differential equations; image thinning; multilayer perceptrons; nonlinear functions; stability; Lyapunov function technique; center point detection; coupling templates; image processing; linear nonseparable task; skeletonizing; stability; symmetric templates; two-layer cellular neural networks; Cellular neural networks; Displays; Image processing; Lyapunov method; Multi-layer neural network; Neural networks; Nonlinear equations; Pattern recognition; Stability; Steady-state;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
ISSN :
1098-7576
Print_ISBN :
0-7803-7278-6
Type :
conf
DOI :
10.1109/IJCNN.2002.1007817
Filename :
1007817
Link To Document :
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