This paper considers the problem of exponential stability analysis of neural networks with time-varying delays. The activation functions are assumed to be globally Lipschitz continuous. A linear matrix inequality (LMI) approach is developed to derive sufficient conditions ensuring the delayed neural
A novel approach to exponential stability of nonlinear systems with time-varying delays
โ Scribed by Song Xueli; Peng Jigen
- Publisher
- Elsevier Science
- Year
- 2011
- Tongue
- English
- Weight
- 212 KB
- Volume
- 235
- Category
- Article
- ISSN
- 0377-0427
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โฆ Synopsis
In this paper, the stability of nonlinear systems with time-varying delays is investigated by means of the concepts of generalized Dahlquist constant, generalized relative Dahlquist constant and relative minimal Lipschitz constant. In detail, two sufficient conditions are derived for the exponential stability of nonlinear systems with time-varying delays and the exponential decay of the solutions is also estimated. Compared with some existing results, our stability conditions are less conservative. Some examples are given to illustrate the effectiveness of the obtained results.
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