Selection of optimal wavelet basis for signal denoising

In order to choose the optimal wavelet basis in the signal processing, the feature of wavelet basis is summarized, based on an analysis of wavelet basis parameter characteristics. Regards the energy-threshold curve as the applicability criterion of wavelet basis. This article introduces reconstruction parameters to evaluate the effectiveness factors of wavelet denoising, and uses translation invariant wavelet Translation Invariant (TI) for signal denoising. Finally, noisy low - frequency signal is tested, experimental results show that the method can accurately identify the fitness for a particular signal of optimum wavelet base, it is practical. Further concludes that the wavelet scale functions of two wavelets bior6.8 and sym8 are rule, wavelet denoising is effect and useful for low frequency signal denoising. Simulation experimental results validate the correctness of the conclusions.