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基于小波变换的去雾处理程序，附有实验图片，可以运行的，希望对大家有帮助！(Based on wavelet transform to fog handler, attached to the experimental images, you can run, I hope it can help you!)

图像处理中，有关二维离散小波变换的PPT例程，富有参考价值。(Image processing related to the two-dimensional discrete wavelet transform PPT routines, full of reference value.)

基于matlab的小波包分解应用于机械振动信号的故障分析(Used in failure analysis of mechanical vibration signals based on the Matlab wavelet packet decomposition)

谐波小波分析的源代码，应该属于信号处理类的，绝对值得收藏，送给朋友们！(Harmonic wavelet analysis source code, it should be under the category of signal processing, and definitely worth collection, a gift my friends!)

小波包分解与重构使用，最佳树使用方法。小波分析理论与MATLAB实现实例。很好的程序，希望对大家有用。(Wavelet packet decomposition and reconstruction using the best tree to use. MATLAB implementation of wavelet analysis theory and examples. Very good program, I hope all of us. )

基于第二代小波的非抽样小波变换应用程序，可以用来小波转换(Non-sampling based on second generation wavelets, wavelet transform application)

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.)

利用小波变换检测回波,经过labview显示，实现了很好的界面效果(Using wavelet transform to detect echoes through labview display interface to achieve a good effect)

很好的继续教育教材，提升素质必备啊！不可错过！十分的好(Good continuing education materials, enhance the quality of essential ah!)

通过设计Visual C程序源码对简单易懂的一维信号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波与Haar小波变换，从而的到小波分解系数；再通过改变分解的到的各层高频系数数进行信号的小波重构达到消噪噪的目的。在这一程序源码实现的过程中能直观地理解信号小波分解重构的过程与在信号消噪中的重要作用，和在对各层高频系数进行权重处理时系数的选取对信号消噪效果的影响。 可直接 (Design Visual C program source code on a simple one-dimensional signal with a Gaussian white noise Daubechies wavelet, Morlet wavelet and Haar wavelet transform, and thus to the wavelet coefficients and then change the decomposition to each storey wavelet reconstruction frequency coefficient of the number of signal to noise canceling noise. In the process of realization of this program source code can be intuitively understood the signal wavelet decomposition and reconstruction process and an important role in signal denoising, and the selection coefficient in the high frequency coefficients of the layers of the weight of processing noise cancellation signal impact. Can be directly)