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本书是“MATLAB应用技术”系列丛书之一，以最新推出的MATLAB中的小波分析工具箱Wavelet Toolbox 3.0版本为基础。全书共分为三部分，第1部分着重介绍了小波理论基础，包括小波基础知识、连续小波变换、离散小波变换、多分辨率分析与正交小波变换、小波变换和多采样滤波器组、二维小波变换与图像处理及小波包的基本原理等；第2部分重点说明了小波分析工具箱的详细使用方法，包括图形用户接口、小波通用函数、一维小波变换的MATLAB实现、二维小波变换的MATLAB实现、小波包变换的MATLAB实现、信号和图像的降噪和压缩，以及最新的信号和图像的提升小波变换等内容；第3部分主要介绍了小波工具箱的应用基础，以及小波变换在语音和生物医学信号处理中、故障诊断中、数字水印中的应用方法。(This book is "MATLAB application technology" Series on one of the latest MATLAB Wavelet toolbox in the Wavelet Toolbox 3.0 version of the basis. The book is divided into three parts, Part 1 focuses on the theory of wavelet basis, including basic knowledge of wavelets, continuous wavelet transform, discrete wavelet transform, multiresolution analysis and orthogonal wavelet transform, wavelet transform and multirate filter banks, 2-dimensional wavelet transform and image processing and the basic principles of wavelet packets, etc. Part 2 highlights the detailed use of wavelet analysis toolbox methods, including graphical user interface, wavelet generic function, one-dimensional wavelet transform MATLAB realization of two-dimensional wavelet transform of the MATLAB implementation of the MATLAB implementation of wavelet packet transform, signal and image noise reduction and compression, and the latest signal and image enhancement of wavelet transform content Part 3 introduces the wavele)

一般最小二乘、递推最小二乘、增广最小二乘用于有色噪声干扰的系统辨识，及辨识结果对比。(General least squares, recursive least squares, extended least squares for the colored noise system identification, and the comparison of recognition results.)

产生信号序列向量st,并显示st的时域波形和频谱 st=mstg 返回三路调幅信号相加形成的混合信号，长度N=800( Generated signal sequence vector st st time-domain waveform and the spectrum st = mstg return three AM signals are added to form the mixed-signal length N = 800)

software for support vector machine

读入mit库的心电信号，并利用小波分析的方法去除其基线漂移(Read ECG mit libraries and to make use of wavelet analysis method to remove the baseline drift)

This tutorial is designed to give the reader an understanding of Principal Components Analysis (PCA). PCA is a useful statistical technique that has found application in fields such as face recognition and image compression, and is a common technique for finding patterns in data of high dimension. Before getting to a description of PCA, this tutorial first introduces mathematical concepts that will be used in PCA. It covers standard deviation, covariance, eigenvectors and eigenvalues. This background knowledge is meant to make the PCA section very straightforward, but can be skipped if the concepts are already familiar.

optimization variable function

北京航空航天大学出版的matlab从零进阶的原程序代码第1章案例21.4源代码(Beijing University of Aeronautics and Astronautics from zero Advanced matlab published the original program code in Chapter 1 Case 21.4 source code)

光学单缝衍射是光学中经常用到的实验，该实验能够很好地模拟光学实验，希望各位好好下载，不懂跟我联系(Single slit diffraction )

matlab仿真关于卡尔曼滤波的源代码 (matlab simulation example )