DenoisewaveletMod

说明：  利用小波变换去除图像中噪声，对比其他去噪方法(Using Wavelet Transform to Remove Noise from Image)

小波变换图像增强程序。以及非线性的处理程序。+MATLAB编译环境(Wavelet transform image enhancement program.And non-linear handlers.+MATLAB compilation environment)

说明：  这是一个关于小波应用工程程序的期末作业，里面包括连续小波变换和离散小波变换，适合初学者使用(This is a project on the application of wavelet end of the operating procedures, including inside the continuous wavelet transform and discrete wavelet transform, for beginners)

用stft、小波变换、EMD分别对突变信号进行时频分析(With stft, wavelet transform, EMD mutations were signals of time-frequency analysis)

某一直升机齿轮箱上的早期损伤的特征是，在伴随振动信号上产生一个可变周期的非平稳扰动信号。要求按此特征构造一组有物理意义的数据仿真早期故障信号，应用小波变换技术分析故障的特征和发生时刻。(a helicopter gearbox early on the characteristics of the injury, In addition to the vibration signal produced a variable cycle perturbation of non-stationary signals. Click here to request a group of tectonic significance of a physical early fault simulation data signals Application of wavelet transform technical analysis of the features and fault occurred moments.)

本人自己编写的小波变换脊提取程序，可用与信号分析．欢迎指导．(I have written wavelet transform ridge extraction procedures, can be used with the signal analysis. Welcomed the guidance.)

几种小波阈值函数去噪的程序及其运行结果比较(Several wavelet threshold denoising function to run the program and its results more)

基于快速小波变换的闪变检测算法，用于计算闪变值(Flicker detection algorithm based on fast wavelet transform )

脉搏信号分析 （1）设计滤波器，实现对脉搏信号的噪声抑制和基线纠漂； （2）时域分析：波形特征检测； （3）功率谱分析：对消噪后的信号进行功率谱分析。要求计算信号的功率谱，功率谱峰值，峰值频率。 (Pulse signal analysis (1) design the filter, to achieve the pulse signal noise suppression and baseline drift correction (2) time-domain analysis: waveform feature detection (3) power spectral analysis: noise cancellation signal after the power spectrum analysis . Require calculation of the signal power spectrum, peak power spectrum, peak frequency.)

这是本人的图像处理作业 包括利用各种基于小波的去噪过程，如硬阈值 软阈值等。。内容很丰富哦！相信一定对你有帮助的！(This is my image processing operations including the use of wavelet-based de-noising process, such as a hard threshold, such as soft-thresholding. . Oh, the content is very rich! I am sure will help you!)