harmwave

基于小波变换的心电信号预处理MATLAB源代码(The heart preprocessind based on wavelet transform)

几种小波阈值函数去噪的程序及其运行结果比较(Several wavelet threshold denoising function to run the program and its results more)

说明：  小波变换技术与工程实践：图像的小波变换(MFC框架下)(Wavelet transform technology and engineering practice: Image Wavelet Transform (MFC framework))

此示意程序用DWT实现二维小波变换 1.调原始图像矩阵 2.进行二维小波分解 3.分解结果显示 重构源图像及结果显示 (This indicated the procedure using two-dimensional wavelet transform DWT realize one. Transferred the original image matrix 2. To carry out two-dimensional wavelet decomposition 3. Decomposition results show that reconstruction of the source images and results show)

说明：  CEEMDAN和EEMD等去噪方法的合集(CEEMDAN/EEMD/EMD:Collection of various denoising methods)

多点目标 单站SAR的回波信号仿真以及BP后向投影成像 参数见合成孔径雷达成像——算法与实现一书表6.1 运行结果正确，注释比较详细(Percent more single station SAR point target echo signal simulation and backward projection imaging BP parameters, see synthetic aperture radar imaging- algorithm and implementation of a book Table 6.1 run result is correct, more detailed notes)

小波变换在图像处理中应用于图像分析，图像压缩，图像去噪等。本文就小波变换理论和matlab语言的小波分析工具箱做了简单阐述。(Wavelet transform in image processing applied to image analysis, image compression, image denoising, etc.. In this paper, wavelet transform theory and wavelet analysis matlab language to do the simple toolbox on.)

文基于小波分析的特点，提出了一种对信号进行多重小波 变换的自适应去噪法，该方法不仅克服了小波去噪软硬阈值法的局限性，而且解决了自适应滤波中参考信号选取难的 问题，将该方法用于脉搏信号降噪，得到了满意的去噪效果。(The text features based on wavelet analysis, proposed an adaptive multi-wavelet transform for signal denoising method, this method not only overcomes the limitations of hard and soft thresholding method of wavelet de-noising, and resolve the reference signal adaptive filtering Select the difficult problem of the method is used to the noise of the pulse signal, and been satisfied with the denoising effect.)

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)

小波基contourlet变换 其中包含spiht编码 去噪 纹理识别(Wavelet transform contourlet transform includes SPIHT coding and denoising texture recognition.)