多时变时滞细胞神经网络的全局渐近稳定

研究了多时变时滞细胞神经网络的全局渐近稳定问题。给出了多时变时滞细胞神经网络平衡点唯一性和全局渐近稳定的几个新充分判据。所研究的网络模型扩展了现有的同类网络模型,而且所得到的这些新稳定判据考虑了神经元激励和抑制的影响,且能够表示成线性矩阵不等式的形式,易于用现有的内点算法等方法验证。通过2个注释说明了所得结果的有效性。

Global asymptotic stability of cellular neural networks with multiple time-varying delays

The global asymptotic stability was discussed for the cellular neural networks(CNN) with multiple time-varying delays.Several new sufficient criteria were given to ascertain the uniqueness and the global asymptotic stability of the equilibrium point for the CNN with multiple time-varying delays.The studied neural networks model expands the existing equivalent models,and the new criteria generalize and improve upon some previous ones.Moreover,the obtained criteria eliminate the effects caused by the neuronal excitatory and the inhibitory,can be expressed in the form of linear matrix inequality,and is easily verified using the recently developed interior-point algorithms.Two remarks were presented to demonstrate the effectiveness and features of the new stability criteria.