Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1706987 | Applied Mathematical Modelling | 2008 | 10 Pages |
Abstract
In this paper, several sufficient conditions are obtained to guarantee that the n-dimensional cellular neural network can have even (⩽2n) memory patterns. In addition, the estimations of attractive domain of such stable memory patterns are obtained. These conditions, which can be directly derived from the parameters of the neural networks, are easily verified. A new design procedure for cellular neural networks is developed based on stability theory (rather than the well-known perceptron training algorithm), and the convergence in the new design procedure is guaranteed by the obtained local stability theorems. Finally, the validity and performance of the obtained results are illustrated by two examples.
Keywords
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Computational Mechanics
Authors
Zhigang Zeng, De-Shuang Huang, Zengfu Wang,