Existence and stability of almost periodic solution for BAM neural networks with delays
Applied Mathematics and Computation
Dynamics of periodic delayed neural networks
Neural Networks
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Neural Processing Letters
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Mathematics and Computers in Simulation
Acta Applicandae Mathematicae: an international survey journal on applying mathematics and mathematical applications
Information Sciences: an International Journal
Dynamics and oscillations of GHNNs with time-varying delay
ICANN'12 Proceedings of the 22nd international conference on Artificial Neural Networks and Machine Learning - Volume Part I
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This paper presents several sufficient conditions about existence, uniqueness and stability of the almost periodic solution of general Hopfield neural networks with time-varying delays using exponential dichotomy, several fixed point theorems, Halanay inequality, Lyapunov functional and some inequality techniques. These results extend and improve some known relevant works, e.g. the restrictions to the connection weight matrices are slacker, and it is not required that the activation functions are globally Lipschitzian. Most importantly, these conditions are easy to check and apply. Finally, one example is employed to illustrate the conclusions, and the simulated results show the validity. Particularly, the right assertion about the existence, uniqueness and stability of the almost periodic solution of the specific generalized Hopfield neural networks is given only by our criteria, and the relevant criteria provided by a recent reference fail.