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Fixed-Time Passification Analysis of Interconnected Memristive Reaction-Diffusion Neural Networks | IEEE Journals & Magazine | IEEE Xplore

Fixed-Time Passification Analysis of Interconnected Memristive Reaction-Diffusion Neural Networks


Abstract:

This article deals with fixed-time passification problem of interconnected networks composed of multiple memristive reaction-diffusion subsystems. Different from the fini...Show More

Abstract:

This article deals with fixed-time passification problem of interconnected networks composed of multiple memristive reaction-diffusion subsystems. Different from the finite-time passivity proposed by Wang, Zhang, et al. (2018), a novel concept of fixed-time passivity/passification is proposed by using upper right Dini derivative, where the settling time is independent on initial value. Next, by designing an appropriate controller and utilizing inequality technique, we put forward several sufficient conditions to guarantee the fixed-time passification of the interconnected memristive reaction-diffusion neural networks (MRDNNs). Furthermore, a fixed-time synchronization criterion is proposed for interconnected MRDNNs. The fixed-time passivity/passification of interconnected MRDNNs has important practical significance in the design and implementation of neural network circuits. Finally, a numerical example is presented to substantiate the correctness of the theoretical results.
Published in: IEEE Transactions on Network Science and Engineering ( Volume: 7, Issue: 3, 01 July-Sept. 2020)
Page(s): 1814 - 1824
Date of Publication: 19 November 2019

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