Introduction to the theory of neural computation
Introduction to the theory of neural computation
Global attractivity in delayed Hopfield neural network models
SIAM Journal on Applied Mathematics
Global exponential stability of delayed Hopfield neural networks
Neural Networks
Stability and bifurcation analysis on a discrete-time neural network
Journal of Computational and Applied Mathematics
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
IEEE Transactions on Neural Networks
Globally asymptotical stability of discrete-time analog neural networks
IEEE Transactions on Neural Networks
Stability analysis of discrete-time recurrent neural networks
IEEE Transactions on Neural Networks
IEEE Transactions on Neural Networks
A delayed neural network for solving linear projection equations and its analysis
IEEE Transactions on Neural Networks
Multiperiodicity of Discrete-Time Delayed Neural Networks Evoked by Periodic External Inputs
IEEE Transactions on Neural Networks
Neural network for quadratic optimization with bound constraints
IEEE Transactions on Neural Networks
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This paper is concerned with boundedness, convergence of solution of a class of non-autonomous discrete-time delayed Hopfield neural network model. Using the inequality technique, we obtain some sufficient conditions ensuring the boundedness of solutions of the discrete-time delayed Hopfield models in time-varying situation. Then, by exploring intrinsic features between non-autonomous system and its asymptotic equations, several novel sufficient conditions are established to ensure that all solutions of the networks converge to the solution of its asymptotic equations. Especially, for case of asymptotic autonomous system or asymptotic periodic system, we obtain some sufficient conditions ensuring all solutions of original system convergent to equilibrium or periodic solution of asymptotic system, respectively. An example is provided for demonstrating the effectiveness of the global stability conditions presented. Our results are not only presented in terms of system parameters and can be easily verified but also are less restrictive than previously known criteria.