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Finite-Time Stabilization for Static Neural Networks with Leakage Delay and Time-Varying Delay

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Abstract

The problem of finite-time stabilization (FTS) for static neural networks (SNNs) with leakage delay and time-varying delay is investigated in this paper. By introducing an auxiliary function and utilizing the Lyapunov stability theory, we derive some sufficient criteria for FTS in terms of linear matrix inequalities (LMIs). Two feedback controllers are designed based on two different Lyapunov functions, which can be easily solved via MATLAB LMI toolbox, to guarantee the FTS for the SNNs. Finally, two numerical examples are given to illustrate the efficiency of our results.

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Correspondence to Yuan Yuan or Xiaodi Li.

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This work was supported by National Natural Science Foundation of China (61673247) and NSERC of Canada (203786 46310 2000) (YY). The paper has not been presented at any conference.

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Zhang, X., Yuan, Y. & Li, X. Finite-Time Stabilization for Static Neural Networks with Leakage Delay and Time-Varying Delay. Neural Process Lett 51, 67–81 (2020). https://doi.org/10.1007/s11063-019-10065-1

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