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Stability of delayed memristive neural networks with time-varying impulses

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Abstract

This paper addresses the stability problem on the memristive neural networks with time-varying impulses. Based on the memristor theory and neural network theory, the model of the memristor-based neural network is established. Different from the most publications on memristive networks with fixed-time impulse effects, we consider the case of time-varying impulses. Both the destabilizing and stabilizing impulses exist in the model simultaneously. Through controlling the time intervals of the stabilizing and destabilizing impulses, we ensure the effect of the impulses is stabilizing. Several sufficient conditions for the globally exponentially stability of memristive neural networks with time-varying impulses are proposed. The simulation results demonstrate the effectiveness of the theoretical results.

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Acknowledgments

This publication was made possible by NPRP Grant # NPRP 4-1162-1-181 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors. This work was also supported by Natural Science Foundation of China (Grant No: 61374078).

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Authors and Affiliations

  1. College of Computer Science, Chongqing University, Chongqing, 400044, China

    Jiangtao Qi & Chuandong Li

  2. Department of Mathematics, Texas A&M University at Qatar, PO Box 23874, Doha, Qatar

    Tingwen Huang

Authors
  1. Jiangtao Qi
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  2. Chuandong Li
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  3. Tingwen Huang
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Correspondence to Chuandong Li.

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Qi, J., Li, C. & Huang, T. Stability of delayed memristive neural networks with time-varying impulses. Cogn Neurodyn 8, 429–436 (2014). https://doi.org/10.1007/s11571-014-9286-0

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  • DOI: https://doi.org/10.1007/s11571-014-9286-0

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