小波变换

这是一款用来分析心率变异性的matlab程序，有线性分析和非线性分析，包含输出结果包含频谱分布、统计学描述、样本熵、小波分析(This is a matlab program used to analyze heart rate variability, linear analysis and nonlinear analysis contains the output contains spectral distribution, statistical description sample entropy, wavelet analysis)

计算小波时间熵的源程序，内容详尽，调试正确，非常有用。计算小波时间熵的源程序，内容详尽，调试正确，非常有用。(Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful. Calculate the entropy of the source wavelet time, detailed, debugging is correct, very useful.)

说明：  故障行波波头识别：模极大值原理识别故障行波波头(Modulus maxima principles identified wave head)

（1）用MATLAB开发的傅立叶变换以及逆变换的一个例子，测试通过无误。（2）C＋＋编写的傅立叶以及逆傅立叶变换程序源代码，测试通过。((1) Using MATLAB development of the Fourier transform and inverse transform an example of the test correct. (2) C++ and inverse Fourier Fourier transform source code, test.)

使用小波变换的图像边缘检测算法(use wavelet transform Edge Detection Algorithm)

用matlab如何实现fft变换，进而得到经过fft变换后的图像(How to implement FFT transformation with MATLAB)

说明：  基于vc++6.0 的图像对比度拉伸操作(vc 6.0 on the image contrast stretching operation)

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.)

利用小波变换对图像去噪，可以运行，并附有详细的说明，本人编写，感觉不错！欢迎共享.(Using Wavelet Transform for Image Denoising, you can run, together with detailed instructions, I prepared, I feel good! Welcome to share.)

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.)