Integration of Sample Entropy and Harmonic Wavelet Decomposition

This text introduces the concept of "Sample Entropy," a metric used to quantify signal complexity. Additionally, it covers "Harmonic Wavelet Decomposition" techniques that enable detailed analysis of frequency characteristics in signals. For those unfamiliar with these concepts, we provide original MATLAB source code for reference and learning purposes. The MATLAB implementation includes: - Sample Entropy calculation function that measures signal regularity using phase space reconstruction and conditional probability comparisons - Harmonic wavelet transform algorithm performing multi-resolution analysis through frequency-domain filtering with exact band segmentation - Integration module that combines entropy features with wavelet coefficients for comprehensive signal characterization Key functions feature: - Automated parameter optimization for entropy calculations - Configurable decomposition levels for wavelet analysis - Visualization tools for both time-frequency distributions and complexity metrics The code structure follows modular design principles, allowing independent usage of entropy calculation and wavelet transformation components while maintaining seamless integration capabilities.