MATLAB Implementation for Calculating Correlation Dimension

I have discovered a MATLAB program that efficiently calculates the correlation dimension - a fundamental metric for quantifying system complexity and chaotic dynamics. This implementation utilizes Grassberger-Procaccia algorithm to estimate dimension from time series data, making it valuable for applications in physics, engineering, and financial analysis. The program incorporates vectorized operations for improved computational efficiency and includes data preprocessing steps to handle varying dataset sizes and complexities. Key functions include phase space reconstruction using time-delay embedding, distance matrix computation, and logarithmic scaling analysis for dimension estimation. Through this implementation, researchers can extract meaningful insights into system dynamics, with the program automatically handling edge cases and providing visualization options for result interpretation. The code structure allows for customization of parameters like embedding dimension and time delay, enabling tailored analysis for specific research requirements.