Journal
SCIENCE CHINA-TECHNOLOGICAL SCIENCES
Volume 59, Issue 3, Pages 387-402Publisher
SCIENCE PRESS
DOI: 10.1007/s11431-016-6006-5
Keywords
switched neural networks; average dwell time; sojourn probability method; exponential stability
Funding
- National Natural Science Foundation of China [61573096, 61272530]
- Natural Science Foundation of Jiangsu Province of China [BK2012741]
- 333 Engineering Foundation of Jiangsu Province of China [BRA2015286]
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This paper is concerned with the exponential H (a) filtering problem for a class of discrete-time switched neural networks with random time-varying delays based on the sojourn-probability-dependent method. Using the average dwell time approach together with the piecewise Lyapunov function technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with random time-varying delays which are characterized by introducing a Bernoulli stochastic variable. Based on the derived H (a) performance analysis results, the H (a) filter design is formulated in terms of Linear Matrix Inequalities (LMIs). Finally, two numerical examples are presented to demonstrate the effectiveness of the proposed design procedure.
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