Genetic optimized algorithms in wavelet thresholding de-noising

Combined with the characteristics of soft and hard thresholding de-noising methods, this paper posed an improved threshold quantifying project, added the estimated factor, used genetic algorithms to optimize the estimated factor, the fitness function is the signal to noise ratio. The improved project applied to the test signal added noise, the result show that this project compares with soft and hard thresholding de-noising methods makes the de-noising better in a certain extent, and it enhances the signal to noise ratio of de-noising signal.