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Exponential stability and periodic solution for fuzzy BAM Neural networks with time varying delays

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Abstract

In this paper, a class of fuzzy BAM neural networks with time varying delays is discussed. By using the properties of M-matrix, Linear Matrix Inequality(LMI) approach and general Lyapunov-Krasovskii functional, some new sufficient conditions are derived to ensure the existence of periodic solutions and the global exponential stability of the fuzzy BAM neural networks with time varying delays. These results have important significance in the design of global exponential stable BAM networks with delays. Moreover, an example is given to illustrate that the conditions of the results in the paper are feasible.

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Authors and Affiliations

  1. Department of Mathematics, Xiangnan University, Chenzhou, 423000, China

    Hong-jun Xiang & Jin-hua Wang

Authors
  1. Hong-jun Xiang
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  2. Jin-hua Wang
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Supported by the National Natural Science Foundation of China (60574043); the Science Foundation of the Education Committee of Hunan Province (06C792; 07C700), the Construction Program of Key Disciplines in Hunan Province, Aid Program for Science and Technology Innovative Research Team in Higher Educational Institutions of Hunan province

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Xiang, Hj., Wang, Jh. Exponential stability and periodic solution for fuzzy BAM Neural networks with time varying delays. Appl. Math. J. Chin. Univ. 24, 157–166 (2009). https://doi.org/10.1007/s11766-009-1861-5

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  • DOI: https://doi.org/10.1007/s11766-009-1861-5

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