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Uniqueness and stability of equilibria of a class of neural networks with applications to the Hopfield model

机译:一类针对Hopfield模型的一类神经网络均衡的唯一性和稳定性

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In this paper, new conditions for the existence and uniqueness of equilibria of a class of continuous-time recurrent nellral networks are established by utilizing the Brouwer fixed point theorem and results from homo topy theory. Also, newcriteria are established for the local and global asymptotic stability of the equilibrium of neural networks with non-symmetric and symmetric interconnecting matrices, respectively. The present results are applied to the Hopfield continuous-time neuralnetworks.
机译:在本文中,通过利用BROROWER固定点定理和HOMO TOPY理论的结果,建立了一类连续时间复发绝经网络的均衡存在和唯一性的新条件。此外,对于具有非对称和对称互连矩阵的神经网络平衡的本地和全局渐近稳定性,分别建立了NewCriteria。本结果应用于Hopfield连续时间神经网络。

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