Source Code for Basic Wavelet Transform Denoising Algorithm
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In speech signal processing, wavelet transform denoising serves as a fundamental and widely used algorithm. This article presents the source code implementation and demonstrates how to achieve it in MATLAB. The implementation typically involves key steps: wavelet decomposition using functions like wavedec, threshold application (soft/hard thresholding) using wthresh, and signal reconstruction through waverec. For beginners, this serves as valuable reference material that illustrates practical signal processing techniques. Additionally, we explore the algorithm's advantages and limitations, along with adaptation and optimization strategies for specific application scenarios. This includes parameter tuning for wavelet types, decomposition levels, and threshold selection methods. We hope this article helps readers gain deeper understanding of wavelet transform denoising and enables effective practical applications through hands-on code implementation.
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