Results 131 to 140 of about 438 (172)

New Conditions on Global Stability of Cohen-Grossberg Neural Networks

Neural Computation, 2003
In this letter, we discuss the dynamics of the Cohen-Grossberg neural networks. We provide a new and relaxed set of sufficient conditions for the Cohen-Grossberg networks to be absolutely stable and exponentially stable globally. We also provide an estimate of the rate of convergence.
Wenlian Lu, Tianping Chen
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Stability of Impulsive Cohen-Grossberg Neural Networks with Delays

2010
In this paper, with assuming global Lipschitz conditions on the activation functions, applying idea of vector Lyapunov function, Young inequality and Halanay differential inequality with delay, the global exponential stability of the equilibrium point for a class of Cohen-Grossberg neural networks with time-varying delays and impulses is investigated ...
Jianfu Yang, Wensi Ding, Fengjian Yang, Lishi Liang, Qun Hong   +4 more
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Global attraction and stability for Cohen–Grossberg neural networks with delays

Neural Networks, 2006
We consider a class of Cohen-Grossberg neural networks with delays. We prove the existence and global asymptotic stability of an equilibrium point and estimate the region of existence. Furthermore, we show that the trajectories of the neural networks with positive initial data will stay in the positive region if the amplification function satisfies a ...
Kening Lu, Daoyi Xu, Zhichun Yang
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Exponential Stability of Cohen-Grossberg Neural Networks with Delays

2005
The exponential stability characteristics of the Cohen-Grossberg neural networks with discrete delays are studied in this paper, without assuming the symmetry of connection matrix as well as the monotonicity and differentiability of the activation functions and the self-signal functions.
Wei Zhang, Jianqiao Yu
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Stability and bifurcation for discrete-time Cohen–Grossberg neural network

Applied Mathematics and Computation, 2006
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Hongyong Zhao, Lei Wang
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Exponential Stability of Stochastic Inertial Cohen–Grossberg Neural Networks

International Journal of Pattern Recognition and Artificial Intelligence, 2023
In this paper, we adopt two methods to study the problem. Initially, directly from the second-order differential equation, we obtain a sufficient condition (SC) for the mean square exponential stability (MSES) of the system at the equilibrium point by constructing a suitable function and applying some properties of calculus.
Yuehong Zhang, Zhiying Li 0002, Wangdong Jiang, Wei Liu   +3 more
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Stability and bifurcation of a Cohen–Grossberg neural network with discrete delays

Applied Mathematics and Computation, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qiming Liu 0002, Rui Xu 0003
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Stability of Stochastic Cohen-Grossberg Neural Networks

2004
Almost sure stability and instability of stochastic Cohen–Grossberg neural networks are addressed in this paper. Our results can be used as theoretic guidance to stabilize neural networks in practical applications when stochastic noise is take into consideration.
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Stability of Cohen-Grossberg Neural Networks with Nonnegative Periodic solutions

2007 International Joint Conference on Neural Networks, 2007
In this paper, we discuss nonnegative periodic solutions for generalized Cohen-Grossberg neural networks. Without assuming strict positivity and boundedness of the amplification functions, the dynamics of periodic Cohen-Grossberg neural networks are studied.
Tianping Chen, Yanchun Bai
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Asymptotic Behavior of Periodic Cohen-Grossberg Neural Networks with Delays

Neural Computation, 2009
Without assuming the positivity of the amplification functions, we prove some M-matrix criteria for the [Formula: see text]-global asymptotic stability of periodic Cohen-Grossberg neural networks with delays. By an extension of the Lyapunov method, we are able to include neural systems with multiple nonnegative periodic solutions and nonexponential ...
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