Article ID Journal Published Year Pages File Type
1707008 Applied Mathematical Modelling 2009 15 Pages PDF
Abstract

This paper is concerned with global robust exponential stability for a class of discrete-time interval bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient criterion is proposed for the global robust exponential stability of discrete-time BAM neural networks which contain uncertain parameters with their values being bounded. The proposed LMI-based results are computationally efficient as they can be easily checked via the LMI toolbox. Finally, two examples are provided to demonstrate the effectiveness of the obtained results.

Related Topics
Physical Sciences and Engineering Engineering Computational Mechanics
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