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C语言实现一维离散小波变换，通过mallat算法实现对一维信号的快速重构和分解。(C language implementation of a one-dimensional discrete wavelet transform, fast algorithm by mallat one-dimensional signal reconstruction and decomposition.)

FMCW调频连续波雷达的测距测角，可以得到很精确的幅值、频率、相位估计，有小波分析的盲信号处理。( FMCW frequency modulated continuous wave radar range and angular measurements, You can get a very accurate amplitude, frequency, phase estimation, There Wavelet Analysis Blind Signal Processing.)

这是小波包程序，好不容易从网上下下的，希望对大家有用！可直接使用。 (Wavelet packet, and finally from the Internet under the hope that useful! Can be used directly.)

数字信号处理C语言程序集。里面包含全部的数字信号处理中各种算法的C程序设计。(Digital Signal Processing C-assemblies. Which contains all of the digital signal processing algorithms in a variety of C programming.)

数字信号处理的c++库，很好的资源，作者很牛，包括数值计算与常用的信号处理分析,例如FFT、小波变换、功率谱估计等(Digital Signal Processing c++ library, a great resource,including numerical analysis and common signal processing，such as FFT, wavelet transform, power spectrum estimation)

一维信号的小波去噪,这是一个很好的基于小波变换的小波去噪，是针对一维的，去噪效果非常好！(1DWT wavelet denoide)

小波分解在图像处理和电能质量分析中应用广泛，本文应用小波分解的方法将高频的暂态信号提取出来，获取暂态信号的特征量，就能够有效地计算暂态信号。(Wavelet decomposition in image processing and power quality analysis is widely used, this application of wavelet decomposition method to extract high-frequency transient signals, to obtain the amount of transient characteristics of the signal, we can effectively calculate the transient signal.)

9/7 二维整数小波变换，可以实现图像的无损恢复。(9/7 two-dimensional integer wavelet transform, you can realize non-destructive restoration of images.)

在理解了离散小波变换的基本原理和算法的基础上，通过设计VC程序对简单的一维信 号在加上了高斯白噪声之后进行Daubechies小波、Morlet小波和Haar小波变换，从而得到小波分解系数；再通过改变分解得到的各层高频系数进行信号的小波重构达到消噪的目的。在这一程序实现的过程中能直观地理解信号小波分解重构的过程和在信号消噪中的重要作用，以及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。(In understanding the basis of discrete wavelet transform basic principles and algorithms, through the design VC program Daubechies wavelet, Morlet wavelet and Haar wavelet transform after a simple one-dimensional signal plus a Gaussian white noise, resulting wavelet coefficients wavelet reconstruction signal again by changing the layers to achieve high-frequency coefficients decomposed noise cancellation purposes. Can intuitively understand wavelet decomposition and reconstruction process and an important role in signal de-noising in the process of implementation of this program, and in the high-frequency coefficients when the weight of the layers selected for signal processing coefficients denoising affected.)

用于折射波处理时的to、θ函数法求界面深度，浅层地震(Used for refraction wave in processing, θ function method to ask interface depth, shallow earthquake)