New discrete memristive hyperchaotic map: modeling, dynamic analysis, and application in image encryption DOI Creative Commons
Fei Yu, Yi-Chen Wu, Xuqi Wang

et al.

Frontiers in Physics, Journal Year: 2025, Volume and Issue: 13

Published: June 5, 2025

With the rapid development of information technology, demand for ensuring data security and privacy protection has become increasingly urgent. The purpose this study is to address limitations existing image encryption methods develop a more secure efficient scheme. To achieve this, we adopt research method that involves constructing new type discrete memristor hyperchaotic map by coupling an upgraded cosine with Cubic map, then conducting in-depth analysis system’s dynamic characteristics using phase diagrams, Lyapunov exponential spectra, bifurcation diagrams confirm its ability reach state. Based on propose scheme, generating high-quality chaotic sequences through excellent effectively scramble diffuse data, also introducing novel forward reverse diffusion strategy in process enhance efficiency. Through experiments various images, verify algorithm’s effectiveness improving strength, reducing leakage risks, security. Finally, results keyspace analysis, histogram correlation entropy demonstrate scheme high practicability, along good application prospects practical value.

Language: Английский

Dynamics analysis and predefined-time sliding mode synchronization of multi-scroll systems based on a single memristor model DOI
Shaohui Yan, Xinyu Wu, Jiawei Jiang

et al.

Chaos Solitons & Fractals, Journal Year: 2025, Volume and Issue: 196, P. 116337 - 116337

Published: April 4, 2025

Language: Английский

Citations

0
Advances in Zeroing Neural Networks: Bio-Inspired Structures, Performance Enhancements, and Applications DOI Creative Commons
Yufei Wang, Cheng Hua, Ameer Hamza Khan

et al.

Biomimetics, Journal Year: 2025, Volume and Issue: 10(5), P. 279 - 279

Published: April 29, 2025

Zeroing neural networks (ZNN), as a specialized class of bio-Iinspired networks, emulate the adaptive mechanisms biological systems, allowing for continuous adjustments in response to external variations. Compared traditional numerical methods and common (such gradient-based recurrent networks), this capability enables ZNN rapidly accurately solve time-varying problems. By leveraging dynamic zeroing error functions, exhibits distinct advantages addressing complex challenges, including matrix inversion, nonlinear equation solving, quadratic optimization. This paper provides comprehensive review evolution model formulations, with particular focus on single-integral double-integral structures. Additionally, we systematically examine existing activation which play crucial role determining convergence speed noise robustness models. Finally, explore diverse applications models across various domains, robot path planning, motion control, multi-agent coordination, chaotic system regulation.

Language: Английский

Citations

0
Advances in Zeroing Neural Networks: Convergence Optimization and Robustness in Dynamic Systems DOI Creative Commons

Xin Zhou,

Bolin Liao

Mathematics, Journal Year: 2025, Volume and Issue: 13(11), P. 1801 - 1801

Published: May 28, 2025

Zeroing Neural Networks (ZNNs), an ODE-based neural dynamics framework, has become a pivotal approach for solving time-varying problems in dynamic systems. This paper systematically reviews recent advances improving the convergence of ZNN models, focusing on optimization fixed parameters, and activation functions. Additionally, structural adaptations fuzzy control strategies have significantly enhanced robustness disturbance rejection capabilities these ZNNs been successfully applied robotic control, demonstrating superior accuracy compared to traditional methods. Future research directions include exploring nonlinear functions, multimodal adaptation strategies, scalability real-world environments.

Language: Английский

Citations

0
New discrete memristive hyperchaotic map: modeling, dynamic analysis, and application in image encryption DOI Creative Commons
Fei Yu, Yi-Chen Wu, Xuqi Wang

et al.

Frontiers in Physics, Journal Year: 2025, Volume and Issue: 13

Published: June 5, 2025

With the rapid development of information technology, demand for ensuring data security and privacy protection has become increasingly urgent. The purpose this study is to address limitations existing image encryption methods develop a more secure efficient scheme. To achieve this, we adopt research method that involves constructing new type discrete memristor hyperchaotic map by coupling an upgraded cosine with Cubic map, then conducting in-depth analysis system’s dynamic characteristics using phase diagrams, Lyapunov exponential spectra, bifurcation diagrams confirm its ability reach state. Based on propose scheme, generating high-quality chaotic sequences through excellent effectively scramble diffuse data, also introducing novel forward reverse diffusion strategy in process enhance efficiency. Through experiments various images, verify algorithm’s effectiveness improving strength, reducing leakage risks, security. Finally, results keyspace analysis, histogram correlation entropy demonstrate scheme high practicability, along good application prospects practical value.

Language: Английский

Citations

0