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Existence and Stability Analysis of Fractional Order BAM Neural Networks with a Time Delay

Existence and Stability Analysis of Fractional Order BAM Neural Networks with a Time Delay
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摘要 Based on the theory of fractional calculus, the contraction mapping principle, Krasnoselskii fixed point theorem and the inequality technique, a class of Caputo fractional-order BAM neural networks with delays in the leakage terms is investigated in this paper. Some new sufficient conditions are established to guarantee the existence and uniqueness of the nontrivial solution. Moreover, uniform stability of such networks is proposed in fixed time intervals. Finally, an illustrative example is also given to demonstrate the effectiveness of the obtained results. Based on the theory of fractional calculus, the contraction mapping principle, Krasnoselskii fixed point theorem and the inequality technique, a class of Caputo fractional-order BAM neural networks with delays in the leakage terms is investigated in this paper. Some new sufficient conditions are established to guarantee the existence and uniqueness of the nontrivial solution. Moreover, uniform stability of such networks is proposed in fixed time intervals. Finally, an illustrative example is also given to demonstrate the effectiveness of the obtained results.
出处 《Applied Mathematics》 2015年第12期2057-2068,共12页 应用数学(英文)
关键词 BAM Neural Networks Caputo FRACTIONAL-ORDER EXISTENCE Fixed Point THEOREMS UNIFORM Stability BAM Neural Networks Caputo Fractional-Order Existence Fixed Point Theorems Uniform Stability
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