| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 756081 | Communications in Nonlinear Science and Numerical Simulation | 2011 | 11 Pages |
Abstract
In this paper, we investigate the robust stability of uncertain fuzzy Markovian jumping Cohen–Grossberg BAM neural networks with discrete and distributed time-varying delays. A new delay-dependent stability condition is derived under uncertain switching probabilities by Takagi–Sugeno fuzzy model. Based on the linear matrix inequality (LMI) technique, upper bounds for the discrete and distributed delays are calculated using the LMI toolbox in MATLAB. Numerical examples are provided to illustrate the effectiveness of the proposed method.
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Authors
R. Sathy, P. Balasubramaniam,