MATLAB Implementation of Wavelet Filtering Program

The article presents a MATLAB-implemented program for wavelet filtering applications. This program can be used for signal filtering processing by applying wavelet transform techniques, which decompose signals into sub-signals at different frequency components. These sub-signals can then be filtered to remove noise or abrupt changes. Wavelet filtering is a commonly used signal processing method with extensive applications across various fields including image processing and speech processing. The MATLAB-based wavelet filtering program offers several advantages, including user-friendly implementation and high flexibility. The program typically utilizes key MATLAB functions such as wavedec() for wavelet decomposition, wthresh() for thresholding operations, and waverec() for wavelet reconstruction. Users can easily adjust parameters like wavelet type (e.g., 'db4', 'sym8'), decomposition level, and thresholding strategies (hard or soft thresholding) according to specific requirements. The algorithm workflow generally involves: signal decomposition using discrete wavelet transform, coefficient thresholding to remove noise components, and signal reconstruction using inverse wavelet transform. This implementation allows researchers and engineers to optimize filtering performance by experimenting with different wavelet families and threshold selection methods, making it particularly suitable for academic research and engineering applications requiring robust signal denoising capabilities.