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Research Article | Open Access

Research on discrete differential solution methods for derivatives of chaotic systems

School of Electronics & Information Engineering, Suzhou University of Science and Technology, Suzhou, Jiangsu, 215009, China
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Abstract

The pivotal differential parameters inherent in chaotic systems hold paramount significance across diverse disciplines. This study delves into the distinctive features of discrete differential parameters within three typical chaotic systems: the logistic map, the henon map, and the tent map. A pivotal discovery emerges: both the mean value of the first-order continuous and discrete derivatives in the logistic map coincide, mirroring a similar behavior observed in the henon map. Leveraging the insights gained from the first derivative formulations, we introduce the discrete n-order derivative formulas for both logistic and henon maps. This revelation underscores a discernible mathematical correlation linking the mean value of the derivative, the respective chaotic parameters, and the mean of the chaotic sequence. However, due to the discontinuous points in the tent map, its continuous differential parameter cannot characterize its derivative properties, but its discrete differential has a clear functional relationship with the parameter μ. This paper proposes the use of discrete differential derivatives as an alternative to traditional derivatives, and demonstrates that the mean value of discrete derivatives has a clear mathematical relationship with chaotic map parameters in a statistical sense, providing a new direction for subsequent in-depth research and applications.

CLC number: 39A12, 39B12, 65P20

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AIMS Mathematics
Pages 33995-34012

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Cite this article:
Pan X. Research on discrete differential solution methods for derivatives of chaotic systems. AIMS Mathematics, 2024, 9(12): 33995-34012. https://doi.org/10.3934/math.20241621

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Received: 15 July 2024
Revised: 21 November 2024
Accepted: 22 November 2024
Published: 15 December 2024
©2024 the Author(s), licensee AIMS Press.

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0)