Chaos Time Series Analysis and Prediction Toolbox

This text introduces Dr. Zhenbo Lu's Chaos Time Series Analysis and Prediction Toolbox (Version 2.9), which contains fully implemented MATLAB source code for chaotic time series processing. The toolbox provides comprehensive functionality for chaos research applications, including phase space reconstruction algorithms, Lyapunov exponent calculation methods, and chaotic time series prediction techniques. Dr. Lu possesses extensive research experience and practical expertise in chaos theory, making this toolbox particularly valuable for researchers in nonlinear dynamics. The implementation includes core algorithms such as Takens' embedding theorem for phase space reconstruction, Wolf's method for Lyapunov exponent computation, and local prediction approaches for chaotic systems. For researchers exploring chaotic phenomena, this toolbox offers significant practical value through its well-documented MATLAB functions that handle critical tasks like time delay estimation, embedding dimension calculation, and nonlinear prediction modeling. The codebase demonstrates professional implementation of chaos analysis methodologies that can substantially enhance research efficiency and provide deeper insights into complex system behaviors.