Wavelet Transform for Speech Signal Denoising with Thresholding
- Login to Download
- 1 Credits
Resource Overview
A MATLAB program implementing wavelet transform for speech signal denoising, featuring threshold optimization, wavelet decomposition, and reconstruction with practical code implementation details
Detailed Documentation
Wavelet transform is a widely used technique in speech signal processing that achieves noise reduction by decomposing signals into different frequency sub-bands and applying thresholding to each sub-band component. This MATLAB program implements denoising through adaptive threshold searching, utilizing wavelet decomposition and reconstruction methods. The implementation includes key functions for multi-level wavelet decomposition (using wavedec), threshold calculation methods (such as Rigorous SURE or minimax threshold selection), coefficient processing with soft/hard thresholding, and signal reconstruction (using waverec). The algorithm effectively preserves speech characteristics while removing noise components through optimized threshold operations on wavelet coefficients at different resolution levels.
- Login to Download
- 1 Credits