机构地区: 武汉理工大学自动化学院
出 处: 《控制理论与应用》 2006年第1期86-88,共3页
摘 要: 利用输入向量来控制细胞神经网络的稳定性.所得结果表明,当输入向量的绝对值大于某个仅仅只与细胞神经网络的物理参数有关的值时,不附加其它任何条件,细胞神经网络是全局指数稳定的.也讨论了输入向量的部分分量的绝对值大于某个仅仅只与细胞神经网络的物理参数有关的值时,细胞神经网络的全局指数稳定性,所得结论推广和改进了某些已有文献的相应结果. Stability of cellular neural networks is studied by using input vector. A threshold, which is only relevant with the parameters of the networks, is identified. If absolute value of input vector is greater than the threshold, the cellular neural network is globally exponentially stable without any other confinement for the parameters of the networks. If a part of input vector is greater than the threshold, a sufficient criterion of stability of the cellular neural networks has also been obtained. The results presented in this paper are the improvement and extension of the existing ones.
领 域: [自动化与计算机技术] [自动化与计算机技术]