Explore MATLAB source code curated for "G_P算法" with clean implementations, documentation, and examples.
This MATLAB program implements the G-P algorithm for correlation calculation using a mex-compiled version of correlation integral computation, bypassing the "temporary separation" method for enhanced computational efficiency.
Code implementations for estimating correlation dimension, including: G-P algorithm (corrint.m) with point-wise correlation integral calculation, Gaussian kernel association algorithm (gka.m) using smooth kernel functions, and Judd algorithm (judd.m) implementing advanced statistical estimation techniques.
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