Nonlinear filtering in data signal denoising

The purpose of this work is to develop a strategy for filtering transmitted (or received) noisy data signals with minimum loss of information, which can be implemented efficiently. This strategy consists of a wavelet domain filtering that combines a discrete wavelet transform based decomposition phase and a wavelet coefficients shrinkage phase. Data-like signals are generated, white noise is added, the results obtained after filtering are evaluated through signal to noise ratios and performed gains. The proposed procedure performs a decomposition of identified noise and tries to find correlation between the data signal and noise. Results for different filtering techniques and differents decompositons are compared.