Research On Application Of Wavelet Analysis In Mutation Signal Processing

There are two very important issues in signal processing,one is the denoising of the signal,and the other is the detection of signal mutation.In real life,the signals we use often have noise,so the important step before signal mutation detection is to correct Research on signal denoising.As the preprocessing stage of signal processing,denoising is an important prerequisite and basis for further processing of signals,and the detection of signal abrupt changes is the basis for signal identification and fault detection.The research on signal processing has been for many years,even though Significant technical results have been achieved in signal mutation detection and signal denoising,but there is still room for in-depth research and analysis,and processing.The generation of wavelets can smoothly and satisfactorily handle and solve these two problems,which has gradually developed into The core hot issues that the majority of experts and scholars attach importance to.This article also conducts in-depth research on the detection of signal mutation and noise removal.This article focuses on the following two aspects:1.Wavelet transform has obvious advantages over Fourier transform in signal processing,but different wavelet transforms have different accuracy and speed for locating singular points.There are many studies on mutation detection,but most of them are limited to the Mallat algorithm to solve singularities.Point location.In order to quickly locate the location of the singular point,this article uses discrete wavelet transform and its fast algorithm for various frequency mutation signals: the Mallat algorithm detects singular points,and compares it with the dyadic wavelet transform and its fast algorithm :à Trous algorithm for mutation detection experiment.The comparative analysis of experimental results shows that the dyadic wavelet transform can be used to decompose the signal in one layer to accurately locate the position of the singular point,while other transformations need to be multi-decomposed to accurately locate.The advanced wavelet transform can locate the position and intensity of the singular point more quickly and accurately than the discrete wavelet transform;2.A detailed analysis of the advantages and disadvantages of the three types of common threshold functions,and full consideration of their shortcomings and desirable points,this article gives a new wavelet threshold function.This article uses the new threshold function to deal with the high-frequency coefficients after the decomposition of the dyadic wavelet transform The noise in the noisy mutation signal is removed.After comparison experiments,it is found that compared with other threshold functions,the new wavelet threshold function is used to remove the noise of the noisy mutation signal;...