A study on ⟨(Q,S,R)-γ⟩$\langle (\mathcal {Q},\mathcal {S},\mathcal {R})-\gamma \rangle$-dissipative synchronisation of coupled reaction–diffusion neural networks with time-varying delays

M. Syed Ali, Quanxin Zhu, S. Pavithra and N. Gunasekaran

International Journal of Systems Science, 2018, vol. 49, issue 4, 755-765

Abstract: This study examines the problem of dissipative synchronisation of coupled reaction–diffusion neural networks with time-varying delays. This paper proposes a complex dynamical network consisting of N linearly and diffusively coupled identical reaction–diffusion neural networks. By constructing a suitable Lyapunov–Krasovskii functional (LKF), utilisation of Jensen's inequality and reciprocally convex combination (RCC) approach, strictly 〈(Q,S,R)-γ〉$\big \langle (\mathcal {Q},\mathcal {S},\mathcal {R})-\gamma \big \rangle$-dissipative conditions of the addressed systems are derived. Finally, a numerical example is given to show the effectiveness of the theoretical results.

Date: 2018
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DOI: 10.1080/00207721.2017.1422814

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