Robust stability analysis for BAM neural networks of neutral type with time-varying delays and linear fractional uncertainties

DOI

10.2991/icmmcce-15.2015.86How to use a DOI?

Keywords

Bidirectional associative memory neural networks; Robust stability; Time-varying delays; Linear fractional form; Lyapunov-Krasovskii functional

Abstract

This paper investigates the problem of robust stability for bidirectional associative memory (BAM) neural networks of neutral type with time-varying delays and linear fractional uncertainties. By employing integral equality and constructing a new Lyapunov-Krasovskii functional, a sufficient criterion is proposed on robust asymptotic stability for a given BAM neural networks with linear fractional uncertainties. The parameters uncertainties are expressed in a linear fractional form, which includes the norm bounded uncertainties as a special case. Numerical examples are provided to illustrate the effectiveness and less conservatism of the main result.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yunxi Zhang
AU  - Jia Liu
AU  - Yongxin Li
PY  - 2015/12
DA  - 2015/12
TI  - Robust stability analysis for BAM neural networks of neutral type with time-varying delays and linear fractional uncertainties
BT  - Proceedings of the 4th International Conference on Mechatronics, Materials, Chemistry and Computer Engineering 2015
PB  - Atlantis Press
SP  - 422
EP  - 427
SN  - 2352-538X
UR  - https://doi.org/10.2991/icmmcce-15.2015.86
DO  - 10.2991/icmmcce-15.2015.86
ID  - Zhang2015/12
ER  -