MATLAB Code Implementation for Chaos Analysis

This article introduces MATLAB programs developed for chaos analysis. These programs can generate various standard chaotic attractors (such as Lorenz, Rössler, and Henon systems) through differential equation solvers or iterative mappings. Key functionalities include phase space reconstruction with optimal parameter selection using false nearest neighbors or mutual information methods, and chaos prediction algorithms like local linear approximation or neural network approaches. The implementations allow analysts to better understand chaotic phenomena through visualization and quantitative metrics. Furthermore, the codebase supports customization for specific application scenarios through modular function design, enabling improved analysis accuracy and computational efficiency through parameter tuning and algorithm optimization. These MATLAB programs serve as valuable tools in chaos analysis research, warranting further investigation and practical application in nonlinear dynamics studies.