Signal Denoising Based On Wavelet Transform

As a new signal processing method, Wavelet analysis decomposed different kinds of frequency element to non-overlapped frequency bands and this method put forwards an effective way to signal filter, signal-noise separating and character picking-up. Based on serious study of wavelet analysis method, the paper suggests two signal de-noising methods according to stochastic noise: maximum de-noising method and threshold de-noising method. Then the paper analyzed the algorithm of two methods and analyzed its simulink result. Especially to threshold de-noising, a method based on orthogonal wavelet analysis and self-adaptive learning algorithm was proposed here. Then the method was introduced to the design and application of biology intelligence mating apparatus. Result shows the de-noising effect is great. At last, wavelet package analysis method was adopted to decompose high frequency w-space. Applying it to signal de-noising and simulink result was given in the paper. Experiment shows that de-noising based on wavelet can get satisfactory result.