Matlab 线性调频（LFM）脉冲压缩雷达仿真,

根据小波变换后的模极大值 重建原始信号(To reconstruct the original signal based on wavelet transform modulus maxima)

由仿真结果时域和频域图可以看出，工频50Hz干扰信号很好被滤除掉，说明所设计的自适应滤波器效果较好。(It can be seen by the domain and frequency domain simulation results in Figure, the frequency 50 Hz interference signals very well be eliminated, the design of the adaptive filter is better.)

用于计算一个实数或复数序列的离散傅里叶变换和一个复数序列的逆离散傅里叶变换(fast fourier transform subroutine for real valued series)

contourlet图像融合的matlab源代码，很有用，毕业设计的参考(contourlet image fusion matlab source code, useful, graduated from the reference)

An Efficient Randomized Algorithm for Detecting Circles

用卷积深度置信网络CDBN的方法来处理睡眠EEG;(use Convolutional deep belief networks to sleep EEG)

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.)

this project by karen lees in 2002 is "image compression by wavelet" 7ayder..eng

对图像进行小波变换的分解和重构的代码，包含以为信号的处理。( The image decomposition and reconstruction of wavelet transform code, including that the processing of the signal.)

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.)