Multistability of HNNs with almost periodic stimuli and continuously distributed delays

Authors:
Zhenkun Huang;Sannay Mohamad;Honghua Bin
Affiliations:
School of Sciences, Jimei University, Xiamen, China;Faculty of Science, Department of Mathematics, Universiti Brunei Darussalam, Gadong, BE, Brunei Darussalam;School of Sciences, Jimei University, Xiamen, China
Venue:
International Journal of Systems Science
Year:
2009

Citing 11
Cited 5

Stability of some test equations with delay

SIAM Journal on Mathematical Analysis
Global stability analysis in delayed Hopfield neural network models

Neural Networks
On the stability analysis of delayed neural networks systems

Neural Networks
Ordinary Differential Equations

Ordinary Differential Equations
Global stability of neural networks with distributed delays

Neural Networks
Dynamic logic a review

AI Magazine
Global asymptotic stability of Hopfield neural network involving distributed delays

Neural Networks
Almost periodic solutions for Hopfield neural networks with continuously distributed delays

Mathematics and Computers in Simulation
Global exponential stability in DCNNs with distributed delays and unbounded activations

Journal of Computational and Applied Mathematics
Exponential stability of impulsive Cohen–Grossberg networks with distributed delays

International Journal of Circuit Theory and Applications
On the Almost Periodic Solution of Cellular Neural Networks With Distributed Delays

IEEE Transactions on Neural Networks

Multistability in networks with self-excitation and high-order synaptic connectivity

IEEE Transactions on Circuits and Systems Part I: Regular Papers
Multiperiodicity of periodically oscillated discrete-time neural networks with transient excitatory self-connections and sigmoidal nonlinearities

IEEE Transactions on Neural Networks
Impulsive hybrid discrete-time Hopfield neural networks with delays and multistability analysis

Neural Networks
Multistability and multiperiodicity of high-order competitive neural networks with a general class of activation functions

Neurocomputing
Multistability analysis: high-order networks do not imply greater storage capacity than first-order ones

ISNN'10 Proceedings of the 7th international conference on Advances in Neural Networks - Volume Part I

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this article, we investigate multistability of Hopfield neural networks (HNNs) with almost periodic stimuli and continuously distributed delays. By employing the theory of exponential dichotomy and Schauder's fixed point theorem, sufficient conditions are gained for the existence of 2N almost periodic solutions which lie in invariant regions. Meanwhile, we derive some new criteria for the networks to converge toward these 2N almost periodic solutions and the domain of attraction is also given. The obtained results are new, general and improve corresponding results existing in previous literature.