Ch10

说明：  可导入comtrade格式录波文件，进行谐波分析(It can import COMTRADE format recording file for harmonic analysis)

说明：  代码主要应用于图像融合的处理方面，包含Matlab在图像方面的工具箱，小波变换算法的源代码（包含多分辨率小波算法，自适应小波算法的研究）等等(Code is mainly used in image fusion processing, the image area contains Matlab toolbox, wavelet transform algorithm source code (including multi-resolution wavelet algorithm, adaptive wavelet algorithm), etc.)

小波变换去噪，软阈值和硬阈值，以及自己的设计的阈值函数来去噪，毕业设计全套。很全面的资料，绝对最全面的资料，我保证(Wavelet denoising, soft thresholding and hard thresholding, as well as design their own threshold denoising function, the design of a full set of graduation. Comprehensive information is absolutely the most comprehensive information, I promise)

利用matlab中的小波变换函数，对图像进行小波降噪，并分析降噪效果。(The wavelet transform using matlab function, the image wavelet noise reduction, and analyze the noise reduction effect.)

EEG采集脑电波，然后用小波变换分析睁眼时产生脑电波的频率及各项数据(EEG brain waves collected and then analyzed using wavelet transform eyes when the frequency of brain waves generated and the data)

对信号进行小波变换，抑制系数小波滤波，采用了硬阈值滤波方法(right signal wavelet transform, wavelet filter coefficients inhibit use of the hard threshold filtering method)

说明：  小波变换算法的C语言实现，包括DWT,INDWT,提升小波，以及小波去噪的MATLAB源代码(wavelet transform algorithm in C language, including DWT, INDWT upgrade wavelet Wavelet denoising and MATLAB source code)

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.)

说明：  采用5/3小波提升算法编写的一维和二维信号小波分解与重构程序。给出了图象分解的演示示例。(using 5/3 wavelet algorithm to enhance the one-and two-dimensional wavelet decomposition and reconstruction process. Given the decomposition of images demonstration examples.)

四元数小波变换。对图像进行四元数小波域变换，并根据变换后得到的四个部分进行幅度相位分析。(Quaternion wavelet transform.Including image analysis via quaternion wavelet domain,such as one magnitude and three angles.)