Wavelet Entropy Extraction Program for Quantitative Feature Evaluation

Resource Overview

This wavelet entropy extraction program calculates entropy values that can serve as quantitative features for evaluation. The implementation includes signal decomposition and entropy computation algorithms.

Detailed Documentation

This wavelet entropy extraction program is designed for quantitative feature evaluation. Entropy serves as a metric to measure information uncertainty and data complexity. The program implements wavelet decomposition to break down signals into different frequency components, followed by entropy calculation algorithms (such as Shannon entropy or approximate entropy) to quantify randomness and pattern characteristics in the data. Key functions include wavelet coefficient extraction, probability distribution computation, and entropy value derivation. This tool facilitates the identification of critical features in datasets, providing a foundation for advanced analysis and applications. We encourage users to leverage this program's capabilities to uncover valuable insights from their data!