Source Code for Eliminating Magnetotelluric Signal Static Effects Based on Wavelet Transform and Empirical Mode Decomposition

This documentation presents a source code implementation for eliminating static effects in magnetotelluric signals through the integration of wavelet transform and empirical mode decomposition (EMD). The program achieves effective static effect removal by first decomposing signals using wavelet transform algorithms (such as discrete wavelet transform with customizable mother wavelets) and subsequently processing the decomposed components through EMD's adaptive signal decomposition technique. Key implementation features include: - Multi-level wavelet decomposition for time-frequency signal analysis - EMD-based intrinsic mode function (IMF) extraction for nonlinear signal processing - Static effect identification through joint time-frequency domain characteristics - Adaptive thresholding mechanisms for component selection and reconstruction The algorithm workflow involves: 1. Signal preprocessing and normalization 2. Wavelet coefficient computation using convolution-based filters 3. EMD sifting process for IMF separation 4. Static effect component identification using statistical criteria 5. Signal reconstruction with noise-reduced components This implementation finds applications in various geophysical domains including: - Exploration geophysics for subsurface imaging - Seismic monitoring systems - Environmental electromagnetic field assessment - Resource exploration data processing The core innovation lies in combining wavelet transform's mathematical framework with EMD's data-driven approach, enhancing processing accuracy through dual-domain analysis. Implementation utilizes matrix operations for efficient signal processing and includes configurable parameters for different geological scenarios. This program significantly improves the reliability of magnetotelluric data interpretation by reducing static distortion artifacts.