pth moment exponential stability of stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays.

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ID: 42553
2018
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Ranked #37 of 55 articles by views in neural networks : the official journal of the international neural network society

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Abstract
Stochastic memristor-based bidirectional associative memory (BAM) neural networks with time delays play an increasingly important role in the design and implementation of neural network systems. Under the framework of Filippov solutions, the issues of the pth moment exponential stability of stochastic memristor-based BAM neural networks are investigated. By using the stochastic stability theory, Itô's differential formula and Young inequality, the criteria are derived. Meanwhile, with Lyapunov approach and Cauchy-Schwarz inequality, we derive some sufficient conditions for the mean square exponential stability of the above systems. The obtained results improve and extend previous works on memristor-based or usual neural networks dynamical systems. Four numerical examples are provided to illustrate the effectiveness of the proposed results.
Reference Key
wang2018pthneural Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Wang, Fen;Chen, Yuanlong;Liu, Meichun;
Journal neural networks : the official journal of the international neural network society
Year 2018
DOI
S0893-6080(17)30259-9
URL
Keywords Keywords not found

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