Global exponential stability for neutral-type BAM neural networks with time-varying delays

Abstract

In this article, the global exponential stability of neutral-type bidirectional associative memory (BAM) neural networks with time-varying delays is analysed by utilizing the Lyapunov–Krasovskii functional and combining with the linear matrix inequality (LMI) approach. New sufficient conditions ensuring the global exponential stability of neutral-type BAM neural networks is obtained by using the powerful MATLAB LMI control toolbox. In addition, an example is provided to illustrate the applicability of the result.

Keywords:

• generalized eigenvalue problems
• global exponential stability
• linear matrix inequality
• Lyapunov–Krasovskii functional
• neutral-type BAM neural networks

2000 AMS Subject Classifications :

• 34K20
• 92B20

Acknowledgements

The work of the authors was supported by UGC, New Delhi under SAP(DRS) sanctioned No. F510/6/DRS/2004 (SAP-1).