Wavelet Soft-Threshold Denoising Processing Method
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This document presents a wavelet soft-threshold denoising processing method, accompanied by a running demonstration program example. This technique effectively reduces noise and enhances signal quality through intelligent thresholding operations. The implementation involves selecting appropriate threshold values and wavelet basis functions to optimize signal processing according to specific application requirements. The core algorithm typically includes: 1) Wavelet decomposition of noisy signals using functions like wavedec(), 2) Threshold application with soft-thresholding function wthresh() that shrinks coefficients toward zero, 3) Signal reconstruction via waverec(). In the demonstration, users can clearly observe the improvement in denoised signals, which helps in understanding and validating the method's effectiveness through visual comparison and quantitative metrics like SNR improvement.
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