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\begin{document}

\title{Global Asymptotic Synchronization of Fractional Order Multi-linked
Memristive Neural Networks with Time-varying Delays via Discontinuous
Control}



\author[1]{Shaofang Wang}%
\author[1]{Lixiang Li}%
\author[1]{Haipeng Peng}%
\author[1]{Yixian Yang}%
\author[2]{Mingwen Zheng}%
\affil[1]{Beijing University of Posts and Telecommunications}%
\affil[2]{Shandong University of Technology}%


\vspace{-1em}



  
  \date{May 29, 2024}


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\begin{abstract}
In this paper, we address the global asymptotic synchronization (GAS)
problem of the Master-Slave fractional order multi-linked memristive
neural networks (FOMMNNs). Firstly, we propose the FOMMNNs which
incorporate the fractional calculus into multi-linked memristive neural
networks (MMNNs) for the first time. Then, by utilizing the fractional
differential inclusions and set-valued mapping theories, the addressed
FOMMNNs with discontinuous state switching at the right-hand side and
time-varying delays are converted into the continuous FOMMNNs. Under the
frameworks of fractional Caputo derivative and fractional Fillipov
solution, by the way of building up appropriate Lyapunov functionals and
utilizing some synchronous analysis technology, several sufficient
criteria ensuring that the Master-Slave FOMMNNs can realize global
asymptotic synchronization (GAS) under two different state-feedback
controllers are obtained.%
\end{abstract}%



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