Hybrid control-based synchronization of fractional-order delayed complex-valued fuzzy neural networks

Li, Jie; Li, Hongli; Yang, Juanping; Yang, Jikai; Zhang, Long

doi:10.1007/s40314-023-02286-x

Cited by 6 publications

(1 citation statement)

References 31 publications

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“…Synchronization is a process wherein two or more systems adjust a given property of their motion. Different types of synchronization phenomena have been numerically observed and experimentally verified in a variety of chaotic systems, such as complete synchronization [1,7], phase synchronization [8,9], anti-phase synchronization [10,11], lag synchronization [12,13], generalized synchronization [14,15] and projective synchronization [16,17].…”

Section: Introductionmentioning

confidence: 99%

Generalized Function Projective Synchronization of Two Different Chaotic Systems with Uncertain Parameters

Zhen

2023

Applied Sciences

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This study proposes a new approach to realize generalized function projective synchronization (GFPS) between two different chaotic systems with uncertain parameters. The GFPS condition is derived by converting the differential equations describing the synchronization error systems into a series of Volterra integral equations on the basis of the Laplace transform method and convolution theorem, which are solved by applying the successive approximation method in the theory of integral equations. Compared with the results obtained by constructing Lyapunov functions or calculating the conditional Lyapunov exponents, the uncertain parameters and the scaling function factors considered in this paper have fewer restrictions, and the parameter update laws designed for the estimation of the uncertain parameters are simpler and easier to realize physically.

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