MATLAB Implementation for Computing Various Common Entropy Measures

The following provides MATLAB source code for computing various common entropy measures. This codebase offers complete functionality including but not limited to multiple entropy calculation methods such as Shannon entropy, significant entropy, entropy rate, and more. The implementation features key algorithmic approaches including probability distribution estimation through histogram analysis or kernel density methods, data discretization techniques for continuous variables, and joint entropy computation using probability matrix operations. Additionally, the code includes essential helper functions for data preprocessing, probability normalization, and entropy validation checks. These well-documented MATLAB scripts are particularly valuable for researchers in information theory and related fields, significantly reducing development time and effort while ensuring computational accuracy through optimized vectorized operations and proper error handling mechanisms.