Delay-Dependent Exponential Stability of Discrete-Time BAM Neural Networks with Time Varying Delays
نویسندگان
چکیده
This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality LMI . Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.
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Delay-Dependent Exponential Stability Criterion for BAM Neural Networks with Time-Varying Delays
⎯By employing the Lyapunov stability theory and linear matrix inequality (LMI) technique, delaydependent stability criterion is derived to ensure the exponential stability of bi-directional associative memory (BAM) neural networks with time-varying delays. The proposed condition can be checked easily by LMI control toolbox in Matlab. A numerical example is given to demonstrate the effectiveness...
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