Adaptive Synchronization of Fractional-Order Complex-Valued Chaotic Neural Networks with Time-Delay and Unknown Parameters

Li, Mei and Zhang, Ruoxun and Yang, Shiping (2021) Adaptive Synchronization of Fractional-Order Complex-Valued Chaotic Neural Networks with Time-Delay and Unknown Parameters. Physics, 3 (4). pp. 924-941. ISSN 2624-8174

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Abstract

The purpose of this paper is to study and analyze the concept of fractional-order complex-valued chaotic networks with external bounded disturbances and uncertainties. The synchronization problem and parameter identification of fractional-order complex-valued chaotic neural networks (FOCVCNNs) with time-delay and unknown parameters are investigated. Synchronization between a driving FOCVCNN and a response FOCVCNN, as well as the identification of unknown parameters are implemented. Based on fractional complex-valued inequalities and stability theory of fractional-order chaotic complex-valued systems, the paper designs suitable adaptive controllers and complex update laws. Moreover, it scientifically estimates the uncertainties and external disturbances to establish the stability of controlled systems. The computer simulation results verify the correctness of the proposed method. Not only a new method for analyzing FOCVCNNs with time-delay and unknown complex parameters is provided, but also a sensitive decrease of the computational and analytical complexity.

Item Type: Article
Uncontrolled Keywords: adaptive synchronization; fractional-order; complex-valued chaotic neural networks; time-delay; unknown complex parameter
Subjects: STM Library > Physics and Astronomy
Depositing User: Managing Editor
Date Deposited: 11 Nov 2022 05:00
Last Modified: 19 Sep 2023 07:17
URI: http://open.journal4submit.com/id/eprint/80

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