小波分解

生成高斯波形脉冲，并求解高斯脉冲的自相关结果(Gaussian pulse waveform is generated, and solve the results of Gaussian pulse autocorrelation)

利用小波分析原理对某信号进行分解与重构，并可提取指定层数上的高、低频信号。(A signal is decomposed and reconstructed by using wavelet analysis principle, and high and low frequency signals can be extracted from the specified number of layers.)

MATLAB实现小波变换中的图像拼接技术，可实现水平拼接(In MATLAB wavelet transform in image stitching technology, can achieve the level of splicing)

基于matlab程序对声音信号进行去噪处理，通过小波包处理及小波分析结合(Matlab program based on the sound signal denoising by wavelet packet processing and wavelet analysis combined)

基于小波变换的信号检测和去噪的matlab源程序 基于小波变换的信号检测和去噪的matlab源程序(Matlab source of the signal detection and denoising based on wavelet transform)

利用小波变换进行改进阈值信号去噪 (Improvement threshold signal denoising using wavelet transform)

小波变换、小波逆变换代码，数字信号处理领域常用(Wavelet transform, wavelet inverse transform code, digital signal processing used)

小波变换程序，用于对一维信号，二维信号进行稀疏变换(wavelet transform)

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.)

离散小波变换在图像处理去噪中的应用 经典文献 IEEE的(ECG signal compression using 2-D DWT Hermite coefficients)