Hopfield型神经网络的全局指数稳定性

Global Exponentially Stability of Hopfield Neural Networks

  • 摘要: 研究了Hopfield型神经网络的全局指数稳定性,就活化函数严格单增和严格单增但增益有界的情况,提出了保证网络全局指数稳定的充分判据。对活化函数严格单增权矩阵对角稳定的情况,以简约的形式,给出网络全局指数稳定的收敛速率。

     

    Abstract: In this paper, the stability of Hopfield neural networks is investigated. Under two different circumstances, with activation functions being strictly increased and activation functions being strictly increased but their gains being limited, this paper put forth the criteria that ensure the global exponential stability of networks. As to the networks whose activation functions are strictly increased and whose neuron connection matrix T is diagonal stable, the exponential convergence rate is given.

     

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