WPandEMD

基于小波变换的图像压缩感知 并且进行OMP重建 对压缩感知的性能与采样点数进行性能分析与比较(Image compression based on wavelet transform perception and the OMP reconstruction performance of compressed sensing and sample analysis and comparison of performance points)

用于进行小波变换，对原始的光谱图像数据进行预处理(Used wavelet transform, the original spectral image data preprocessing)

基于小波变换的通信信号码元速率估计.pdf(Estimated rate based on the communication signal element wavelet transform. Pdf)

说明：  python实现小波和短时傅里叶变换，源代码和测试算例(Python implementation of wavelet and short time Fourier transform)

心电图(ECG)是临床上诊断心血管疾病的重要方法。 数字滤波作为数字信号处理技术的重要组成部分，广泛应用于诸如信号分离、恢复、整形等多种场合中。为了使信号不失真及在可编程逻辑器件中容易实现，采用具有严格线性相位特性的FIR滤波器进行低通滤波（0-150Hz），用整系数梳状滤波器来去工频干扰及基线漂移,从而达到对心电信号进行预处理的目的。(Electrocardiogram (ECG) is an important method for clinical diagnosis of cardiovascular diseases. As an important part of digital signal processing technology, digital filtering is widely applied to many occasions, such as signal separation, recovery, shaping and so on. In order to make the signal undistorted and easy to be realized in programmable logic device, the FIR filter with strict linear phase characteristics is used for low pass filtering (0-150Hz), and the entire coefficient comb filter is used to get the interference of the power frequency and the baseline drift, thus the purpose of preprocessing the ECG signal is achieved.)

MORLET小波分析在MATLAB的环境下 适合初学者(MORLET waveLET ANYSIS)

dual tree complex wavelet transform

在labview中进行小波分析程序设计，内容最全、最好的文件，参照本文件可以直接一步步编写小波分析程序，适合初学者。(The labview wavelet analysis program design, the most comprehensive, best file reference in this document can step directly Step preparation of a wavelet analysis program for beginners.)

小波变换的程序包括小波变化 小波分解小波包分解程序(Wavelet transform procedures include wavelet transform wavelet decomposition wavelet packet decomposition program)

小波变换(wavelet transform，WT)是一种新的变换分析方法，它继承和发展了短时傅立叶变换局部化的思想，同时又克服了窗口大小不随频率变化等缺点，能够提供一个随频率改变的"时间-频率"窗口，是进行信号时频分析和处理的理想工具。它的主要特点是通过变换能够充分突出问题某些方面的特征，能对时间(空间)频率的局部化分析，通过伸缩平移运算对信号(函数)逐步进行多尺度细化，最终达到高频处时间细分，低频处频率细分，能自动适应时频信号分析的要求，从而可聚焦到信号的任意细节，解决了Fourier变换的困难问题，成为继Fourier变换以来在科学方法上的重大突破。(Wavelet transform (WT) is a new transform analysis method. It inherits and develops the idea of localization of short-time Fourier transform and overcomes the shortcomings that window size does not vary with frequency. It can provide a frequency-dependent The Time-Frequency window is ideal for time-frequency analysis and processing of signals. Its main feature is that by transforming some features that can fully highlight some aspects of the problem, the localization of the time (space) frequency can be analyzed, and the signal (function) can be gradually and multi-scale refined by the scaling operation, finally reaching the high frequency Time subdivision, frequency subdivision at low frequencies, can automatically adapt to the requirements of time-frequency signal analysis, which can focus on any details of the signal to solve the difficulties of Fourier transform has become a major breakthrough in the scientific method since Fourier transform.)