Wavelet Soft Threshold Denoising Simulink Model

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Resource Overview

This Simulink model implements wavelet soft threshold denoising, performing wavelet decomposition on noisy speech signals to obtain high-frequency and low-frequency coefficients. The model processes these coefficients with thresholding techniques before reconstructing them to produce denoised speech output, effectively reducing noise while preserving speech quality.

Detailed Documentation

This Simulink model processes noisy speech signals through wavelet-based denoising. The implementation begins with wavelet decomposition of the input signal, which separates it into high-frequency and low-frequency coefficients using wavelet transform functions. These coefficients then undergo soft threshold processing, where coefficients below a specified threshold are attenuated while preserving significant signal components through nonlinear shrinkage functions. Finally, inverse wavelet reconstruction synthesizes the processed coefficients back into a clean speech signal. The model effectively reduces noise interference while maintaining speech clarity through this multi-stage processing approach, making it suitable for real-time audio enhancement applications.

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