Explore MATLAB source code curated for "关联维" with clean implementations, documentation, and examples.
Applications of Lyapunov exponents, correlation dimension, and Kolmogorov entropy in chaotic dynamical systems by Chen and colleagues, with code implementation insights
The G-P (Grassberger-Procaccia) method for chaotic time series analysis, used to calculate correlation dimension and embedding dimension required for phase space reconstruction with implementation insights
MATLAB implementation of G-P algorithm for correlation dimension (enhanced version with mex function, ultra-fast performance)----------------------------------- Key Update: Introduction of temporary separation threshold parameter - when set larger than the sequence's average period, it eliminates correlations between consecutive points on the same trajectory, ensuring linear ln r - ln C(r) relationship at small r values
Analysis of chaotic time series features using G-P algorithm for correlation dimension computation, with MATLAB implementation and code optimization techniques
This comprehensive resource covers extensive tools including correlation dimension analysis, information content measurement, GP algorithm implementations, and entropy calculations. Each problem type is approached with multiple methodologies for comparative analysis, featuring Lorenz system algorithms. Represents curated results from systematic organization efforts.
Implementation and simulation of chaotic time series prediction methods, featuring time delay selection, correlation dimension calculation, and maximum Lyapunov exponent estimation algorithms
Grassberger-Procaccia Method Implementation for Correlation Dimension and Embedding Dimension Estimation in Chaotic Systems