wavelet-package

说明：  提出了一种基于复解析小波变换的相位诊断齿轮故障的方法。复解析小波变换将Hilbert变换与小波分析紧密结合在一起,具有自适应分析能力。利用复解析小波变换得到齿轮振动信号的相位,其功率谱图上可提取调制边频带结构来识别故障模式。试验结果表明这种方法可有效应用于齿轮局部故障诊断中。(A new method using the phase based on complex analytical wavelet transform for fault diagnosis of gears was proposed. The phase of vibration signals of gears is got by complex analytical wavelet transform, which combines Hilbert transform with wavelet transform tightly and possesses adaptive analysis ability. By making spectrum analysis of the phase, the sideband structure in power spectrum can be protruded, and the fault pattern can be identified. Experimental results show that the proposed method is effective in local defect detection of gears.)

图像的5/3小波变换的matlab代码。程序简短，易懂。(Image 5/3 wavelet transform matlab code. Program brief and easy to understand.)

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its c-wavelet transform

用于产生各种多小波滤波器系数的程序，包括Cl2小波，GHM多小波等等，很好用(Used to produce a variety of multi-wavelet filter coefficients procedures, including Cl2 wavelet, GHM multiwavelet and so on, very good use)

本书简明扼要地介绍了时间序列及其相关领域的基本概念和基本理论，对ARMA序列预测、时间序列的统计分析、时间序列的时频分析和时间序列的小波变换等给出了有关分析计算方法，结合MATLAB编程应用，介绍了MATLAB时间序列分析有关函数的功能和用法，阐述了如何利用这些函数解决工程应用中的问题。(This book succinctly describes the time sequence and its related fields of basic concepts and theories of the ARMA series forecasting, time series statistical analysis, time series analysis and time-frequency wavelet transform of time series analysis and calculation are given about methods, combined with MATLAB programming applications, the introduction of time series analysis MATLAB functions about functions and usage, explains how to use these functions to solve engineering problems in the application.)

实现f-k变换，功能强大，各种滤波处理，地震波等都能用(wavelet transformF -k transform, powerful, a variety of filtering, seismic waves can be used)

该程序可以实现对信号的小波分解、重构及各频带能量比分析(The program can achieve signal wavelet decomposition and reconstruction and the band energy than)

一个提升小波变换的matlab工具包。可以实现97，53，haar等系列的提升小波分解与重构。(an upgrade wavelet transform Matlab tool kit. 97,53 can be achieved, haar series of lifting wavelet decomposition and reconstruction.)

本程序应用小波变换进行电力系统的在线监测。电力系统在线监测中的检测信号含有大量的背景噪声，不便于检测。应用小波变换解决这一问题。程序中应用db3小波对信号进行5层分解，并得出了各层的细节信号与逼近信号。(This procedure based on wavelet transform power-line monitoring system. Online monitoring of power system test signal contains a lot of background noise, not easy to detect. Application of wavelet transform to resolve this problem. Application procedures for db3 wavelet signal decomposition layer 5, and arrive at different levels of detail signal and approximation signal.)