New stability criteria for BAM neural networks with time-varying delays |
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Authors: | Liang Hao Yingbo |
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Affiliation: | aSpace Control and Inertial Technology Research Center, Harbin Institute of Technology, Harbin 150001, China;bDepartment of Automation Measurement and Control, School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China |
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Abstract: | In this paper, the exponential stability is investigated for a class of time-delay BAM neural networks (NNs). Time delays of two layers are taken into account separately rather than as a whole with the idea of delay fractioning. Then we generalize the result to time-varying interval delay condition. Exploiting the known constant part of delay sufficiently to estimate the upper bounds, we can derive an improved stability for BAM NNs with time-varying interval delay. Two examples are provided to demonstrate the less conservatism and effectiveness of the proposed linear matrix inequality (LMI) conditions. |
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Keywords: | BAM neural networks Delay-dependence Stability Interval delay Linear matrix inequality Time-delay fractioning |
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