2) globally exponential stability
全局指数稳定
1.
New sufficient conditions of globally exponential stability of generalized neural networks with time delays were presented by using Liapunov algorithm,linear matrix inequality and integral inequality.
对于具有时滞的广义神经网络,利用Liapunov函数方法、线性矩阵不等式以及积分不等式等技巧,给出了该神经网络模型的平衡点的存在性、惟一性以及全局指数稳定的一些充分条件。
2.
Using the technique by virtue of Young and Halanay inequalities,some new sufficient criteria are given to ensure the uniqueness of equilibrium point and globally exponential stability.
针对一类多时变时滞细胞神经网络,利用Young不等式和Halanay不等式技术,给出了保证平衡点惟一性和全局指数稳定性的几个充分判据。
3.
Employing the extended Halanay s delay differential inequality and Lyapunov functions, we study globally exponential stability of equilibrium states of cellular neural networks with time-varying delays.
本文利用Halanny时滞微分不等式和Lyapunov函数来研究具有可变时滞的细胞神经网络的平衡状态的全局指数稳定性,得到了不依赖于含任何未知函数存在性的简便代数判据,为实际应用提供方便。
3) global exponential stability
全局指数稳定性
1.
Periodic Solutions、Almost Periodic Solutions and Global Exponential Stability for Cellular Neural Networks with Delays;
时滞细胞神经网络的周期解、概周期解和全局指数稳定性
2.
Based on the relationship between matrix and symmetric matrix global exponential stability of the discrete-time neural networks model and the result of exponential convergence rate were obtained by using the characteristics of eigenvalues of a positive definite matrix and introducing a proper factor.
利用矩阵与对称矩阵的关系和正定矩阵特征值的性质,通过引入一个适当的因子,得到了该离散型神经网络模型是全局指数稳定性和指数收敛率的结果。
3.
Based on the extended Hanalay s inequality and the upper-right derivative,the global exponential stability for the second order Hopfield neural networks with time delays was investigated.
在不要求连接权矩阵的对称性和输入输出函数的可微性与单调性,只要求系统的参数满足是一个M矩阵的情况下,利用推广的Hanalay不等式和上右导数导得系统全局指数稳定性的若干充分条件。
4) globally exponential stability
全局指数稳定性
1.
The existence,uniqueness and globally exponential stability of the equilibrium point of a dynamic neural network with distributed delays were studied without assumption of boundedness and differentiability of activation functions.
在没有假定激励函数有界、可微的情况下,研究包含分布时滞的动态神经网络平衡点的存在性、唯一性和全局指数稳定性。
2.
By using Brouwer s fixed theorem, generalized Halanay s delay differential inequality and Dini s derivative, the existence of stationary point and globally exponential stability of recurrent neural networks with time-varying delay are studied.
利用Brouwer不动点定理,推广的Halanay时延微分不等式及Dini导数,讨论了具有变时滞循环神经网络模型的平衡点的存在性和全局指数稳定性,在不要求激活函数连续可导的条件下,得到了非常简单实用的判别条件。
3.
This paper studies the problem of globally exponential stability for the cellular neural networks.
综合运用矩阵范数、算子测度以及 Lyapunov函数法 ,讨论了细胞神经网络的全局指数稳定性 ,给出了一些较简洁的新的充分判据。
5) global exponential stability
全局指数稳定
1.
This paper studies the existence and global exponential stability of equilibrium for high-order neural networks with time-varying delays.
文章首先利用Brouwer不动点定理得到了平衡点存在性的充分条件,然后利用不等式分析技巧得到平衡点的唯一性及全局指数稳定性的一个新的判据。
2.
In the paper,under the hypothesis that the nonlinear neural active fanctions are Lipschtz condition,the global exponential stability is stuied for the following class of delay Hopfield neural networks by a Lapunov functional and applying inequality:xi(T)=-cixi(t)+n∑j+1aijfj(xj(t))+n∑ijbjfj(xj(t-τj))+Ii,1,2,…,n.
在非线性神经激励函数是Lipschitz条件下,通过引入Lyapunov函数,用不等式等方法,得到了该系统的平衡点是全局指数稳定的条件。
3.
The dynamics—the global exponential stability of the competitive neural networks with different time scales is mainly discussed.
主要考察了一类动态系统——带有不同时间尺度竞争神经网络的全局指数稳定性问题。
6) exponential stability
全局指数稳定性
1.
Some new sufficient conditions for the existence and global exponential stability of a unique equilibrium of the impulsvie delayed model were obtained,without assuming monotonicity or differentiability of the activation functions and subjected to impulsvie state at fixed time.
研究了一类新的具有脉冲的时滞Hopfield神经网络系统模型,引入了新的脉冲条件,在不假设激励函数的可微性、单调性的条件下,得到了系统平衡点的存在性、唯一性及全局指数稳定性的充分条件和指数收敛速率,且所得结果改进了一些已知文献的结论。
2.
With the theory of fixed point and delay differential inequality,some sufficient condtions for existence and uniqueness of equilibrum and global exponential stability of the delay Cohen-Grossberg neural networks are obtained.
给出判定模型平衡点存在唯一性和全局指数稳定性的几个充分条件,这些条件取消了权矩阵(Tij)n×n对称性的假设,推广了已知文献的一些结果,使模型的应用范围更加广泛。
3.
The global exponential stability of cell neural networks with time-varying delays is discussed.
利用矩阵测度、Liapunov函数和Halanay时滞不等式的方法研究了具有变时滞的细胞神经网络模型平衡点的全局指数稳定性问题。
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