In this paper, without assuming the boundedness, monotonicity and differentiability of the activation functions, the conditions ensuring existence, uniqueness, and global asymptotical stability of the equilibrium poin...In this paper, without assuming the boundedness, monotonicity and differentiability of the activation functions, the conditions ensuring existence, uniqueness, and global asymptotical stability of the equilibrium point of Hopfield neural network models with distributed time delays are studied. Using M-matrix theory and constructing proper Liapunov functionals, the sufficient conditions for global asymptotic stability are obtained.展开更多
This paper is the first to introduce the Artificial Neural Network(ANN) theory and techniques in the aggregation and stability analysis of large scale dynamic system with time delays.It presents a new intelligent meth...This paper is the first to introduce the Artificial Neural Network(ANN) theory and techniques in the aggregation and stability analysis of large scale dynamic system with time delays.It presents a new intelligent method of the aggregation and stability analysis for large scale system with time delays. The method proposed in this paper can be used not only on linear constant large scale systems with time delays, but also on times-varying large scale systems with multi-group real time delays. Simulation results show the effectiveness of the method.展开更多
Without the linear growth condition, by the use of Lyapunov function, this paper estab- lishes the existence^and-uniqueness theorem of global solutions to a class of neutral stochastic differen- tim equations with unb...Without the linear growth condition, by the use of Lyapunov function, this paper estab- lishes the existence^and-uniqueness theorem of global solutions to a class of neutral stochastic differen- tim equations with unbounded delay, and examines the pathwise stability of this solution with general decay rate. As an application of our results, this paper also considers in detail a two-dimensional unbounded delay neutral stochastic differential equation with polynomial coefficients.展开更多
In this paper, the influence of the noise and delay upon the stability property of reaction-diffusion recurrent neural networks （RNNs） with the time-varying delay is discussed. The new and easily verifiable conditio...In this paper, the influence of the noise and delay upon the stability property of reaction-diffusion recurrent neural networks （RNNs） with the time-varying delay is discussed. The new and easily verifiable conditions to guarantee the mean value exponential stability of an equilibrium solution are derived. The rate of exponential convergence can be estimated by means of a simple computation based on these criteria.展开更多
基金Supported by the National Natural Science Foundation of China(No.59935100)
文摘In this paper, without assuming the boundedness, monotonicity and differentiability of the activation functions, the conditions ensuring existence, uniqueness, and global asymptotical stability of the equilibrium point of Hopfield neural network models with distributed time delays are studied. Using M-matrix theory and constructing proper Liapunov functionals, the sufficient conditions for global asymptotic stability are obtained.
文摘This paper is the first to introduce the Artificial Neural Network(ANN) theory and techniques in the aggregation and stability analysis of large scale dynamic system with time delays.It presents a new intelligent method of the aggregation and stability analysis for large scale system with time delays. The method proposed in this paper can be used not only on linear constant large scale systems with time delays, but also on times-varying large scale systems with multi-group real time delays. Simulation results show the effectiveness of the method.
基金Supported by National Natural Science Foundation of China （Grant No. 11001091） and Chinese University Research Foundation （Grant No. 2010MS129）
文摘Without the linear growth condition, by the use of Lyapunov function, this paper estab- lishes the existence^and-uniqueness theorem of global solutions to a class of neutral stochastic differen- tim equations with unbounded delay, and examines the pathwise stability of this solution with general decay rate. As an application of our results, this paper also considers in detail a two-dimensional unbounded delay neutral stochastic differential equation with polynomial coefficients.
文摘In this paper, the influence of the noise and delay upon the stability property of reaction-diffusion recurrent neural networks （RNNs） with the time-varying delay is discussed. The new and easily verifiable conditions to guarantee the mean value exponential stability of an equilibrium solution are derived. The rate of exponential convergence can be estimated by means of a simple computation based on these criteria.
