G lobalExponential Stability ofHopfield NeuralNetworks

TANXiao-hui; ZHANG Ji-ye; YANG Yi-ren

Volume 18 Issue 3

Jun. 2005

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Article Contents

Journal of Southwest Jiaotong University > 2005 > 18(3): 338-342.

TANXiao-hui, ZHANG Ji-ye, YANG Yi-ren. G lobalExponential Stability ofHopfield NeuralNetworks[J]. Journal of Southwest Jiaotong University, 2005, 18(3): 338-342.

Citation:

TANXiao-hui, ZHANG Ji-ye, YANG Yi-ren. G lobalExponential Stability ofHopfield NeuralNetworks[J]. Journal of Southwest Jiaotong University, 2005, 18(3): 338-342.

TANXiao-hui, ZHANG Ji-ye, YANG Yi-ren. G lobalExponential Stability ofHopfield NeuralNetworks[J]. Journal of Southwest Jiaotong University, 2005, 18(3): 338-342.

Citation:

TANXiao-hui, ZHANG Ji-ye, YANG Yi-ren. G lobalExponential Stability ofHopfield NeuralNetworks[J]. Journal of Southwest Jiaotong University, 2005, 18(3): 338-342.

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G lobalExponential Stability ofHopfield NeuralNetworks

Publish Date: 25 Jun 2005

Abstract

Abstract

The existence, uniqueness of the equilibrium point of a class ofHopfield neural networks were studied by introducing nonlinearmeasures. The activation function is nonlinear and notnecessary to be continuous, monotone and bounded. Some sufficient conditions and convergence estimation for global exponential stability ofneuralnetworkswere obtained.
- neuralnetworks,
- stability,
- global stability,
- nonlinearmeasures