Existence and Stability of Periodic Solutions for BAM Neural Networks with Time-Varying Delays and Impulses

Authors:
Chunxue Wu;Bao Shi
Affiliations:
Institute of Applied Mathematics, Naval Aeronautical and Astronautical University, Yantai, Shandong, P R China 264001 and School of Mathematics and Information, Yantai University, Yantai, Shandong ...;Institute of Applied Mathematics, Naval Aeronautical and Astronautical University, Yantai, Shandong, P R China 264001
Venue:
ISNN '09 Proceedings of the 6th International Symposium on Neural Networks on Advances in Neural Networks
Year:
2009

Citing 4
Cited 0

On delayed impulsive Hopfield neural networks

Neural Networks
Global exponential stability in continuous-time and discrete-time delayed bidirectional neural networks

Physica D
Global exponential stability of impulsive high-order BAM neural networks with time-varying delays

Neural Networks
Periodic solution for nonautonomous bidirectional associative memory neural networks with impulses

Neurocomputing

Quantified Score

Hi-index	0.00

Visualization

Abstract

By using the continuation theorem of Mawhin's coincidence degree theory, some new sufficient conditions are obtained for the existence and stability of periodic solution of BAM neural networks with variable delays and impulses, and without requirement of the boundedness of the activation functions.