One-Dimensional Signal Denoising Using Modulus Maximum Algorithm

This program implements a modulus maximum-based algorithm for denoising one-dimensional signals, utilizing the classical alternating projection method for signal reconstruction. The primary objective is to enhance signal quality and accuracy by effectively removing noise components. During the denoising process, the algorithm compares signal modulus maxima with noise characteristics and applies specific thresholding rules to adjust the wavelet coefficients. The implementation involves wavelet decomposition to extract modulus maxima, followed by noise threshold application and signal reconstruction through iterative alternating projections between time-frequency domains. This approach effectively reduces noise interference while preserving important signal features, resulting in cleaner and more accurate signal representations. The key functions include wavelet transform computation, modulus maxima detection, threshold optimization, and projection-based reconstruction algorithms.