Literature DB >> 27626965

Exponential Stability of Almost Periodic Solutions for Memristor-Based Neural Networks with Distributed Leakage Delays.

Changjin Xu1, Peiluan Li2, Yicheng Pang3.   

Abstract

In this letter, we deal with a class of memristor-based neural networks with distributed leakage delays. By applying a new Lyapunov function method, we obtain some sufficient conditions that ensure the existence, uniqueness, and global exponential stability of almost periodic solutions of neural networks. We apply the results of this solution to prove the existence and stability of periodic solutions for this delayed neural network with periodic coefficients. We then provide an example to illustrate the effectiveness of the theoretical results. Our results are completely new and complement the previous studies Chen, Zeng, and Jiang ( 2014 ) and Jiang, Zeng, and Chen ( 2015 ).

Mesh:

Year:  2016        PMID: 27626965     DOI: 10.1162/NECO_a_00895

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  3 in total

1.  Stability Analysis for Memristor-Based Complex-Valued Neural Networks with Time Delays.

Authors:  Ping Hou; Jun Hu; Jie Gao; Peican Zhu
Journal:  Entropy (Basel)       Date:  2019-01-28       Impact factor: 2.524

2.  Mean almost periodicity and moment exponential stability of semi-discrete random cellular neural networks with fuzzy operations.

Authors:  Sufang Han; Guoxin Liu; Tianwei Zhang
Journal:  PLoS One       Date:  2019-08-07       Impact factor: 3.240

3.  New exploration on bifurcation for fractional-order quaternion-valued neural networks involving leakage delays.

Authors:  Changjin Xu; Zixin Liu; Chaouki Aouiti; Peiluan Li; Lingyun Yao; Jinling Yan
Journal:  Cogn Neurodyn       Date:  2022-01-30       Impact factor: 3.473

  3 in total

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