A new stability criterion of neutral neural networks with time-varying delays

Luo, R.; Xu, H.; Wang, W.; Wang, Xiangyu

Access Status

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Authors

Luo, R.

Xu, H.

Wang, W.

Wang, Xiangyu

Date

2016

Type

Conference Paper

Metadata

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Citation

Luo, R. and Xu, H. and Wang, W. and Wang, X. 2016. A new stability criterion of neutral neural networks with time-varying delays, In Proceeedings of the International Conference on Applications and Mathematical Analysis in Engineering and Science (AMAES), pp. 487-496.

Source Title

PACIFIC JOURNAL OF OPTIMIZATION

Source Conference

International Conference on Applications and Mathematical Analysis in Engineering and Science (AMAES)

ISSN

1348-9151

School

Department of Construction Management

URI

http://hdl.handle.net/20.500.11937/53984

Collection

Curtin Research Publications

Abstract

In this paper, we study the global stability problem for neutral neural networks with time delays. Firstly, we extend the existing neutral networks to a much general class of such networks. Then, by constructing suitable Lyapunov-Krasovskii-type functionals and using linear matrix inequality (LMI) optimization techniques, we obtain new sufficient conditions for global asymptotic stability of the neural networks. The obtained results are related to some positive real-value parameters rather than positive symmetric matrices which are much complicated computationally. Finally, we demonstrate the results' validity via a numerical example and its simulations.