Wavelet Transform Modulus Maxima Implementation

This implementation features a robust algorithm for identifying wavelet transform modulus maxima, which serves as a fundamental approach for signal singularity detection and multi-scale edge analysis. The core functionality employs continuous wavelet transform combined with local maxima detection across multiple scales to characterize signal features effectively. The code has undergone comprehensive debugging and currently operates with stable performance. Key components include: - Scale-adaptive wavelet coefficient computation - Ridge detection algorithms for tracking maxima across scales - Noise robustness considerations in maxima identification We actively encourage the research community to provide valuable insights and suggestions for further enhancements. Potential areas for optimization include computational efficiency improvements for large-scale data processing, advanced thresholding techniques for better noise immunity, and expanded wavelet family support. This tool represents significant value for signal processing applications, particularly in feature extraction and singularity analysis. We remain committed to iterative development and refinement based on collective expertise. All constructive feedback regarding algorithm efficiency, code structure, or additional functionalities is genuinely appreciated. Acknowledgements for your professional engagement and support in advancing this computational methodology.