Wavelet Modulus Maxima Source Code

This repository contains the Wavelet Modulus Maxima source code, which provides fundamental implementations for wavelet-based denoising and modal parameter identification tasks. Developed by Stanford University researchers, this codebase leverages wavelet transform algorithms to detect modulus maxima points that represent significant signal features. The implementation includes core functions for multi-scale analysis, threshold-based noise reduction, and singularity detection through wavelet coefficient examination. This source code serves as a valuable tool for both academic research and practical applications in signal processing. Users can easily implement wavelet transform operations, filtering techniques, and feature extraction methods using the provided modular functions. The implementation likely includes algorithms for continuous/discrete wavelet transforms, modulus calculation across scales, and local maxima tracking for signal characterization. Researchers and developers can utilize this foundation to build advanced signal processing applications, conduct wavelet analysis studies, or integrate wavelet-based features into larger systems. The code's academic origin ensures methodological rigor while maintaining practical usability for real-world signal processing challenges.