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于 2011-05-16 发布文件大小:9KB

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代码说明：

用stft、小波变换、EMD分别对突变信号进行时频分析(With stft, wavelet transform, EMD mutations were signals of time-frequency analysis)

文件列表：

时频分析
........\hhtnlp1.m,745,2009-10-11
........\HHTsp.m,1004,2009-10-14
........\m.m,352,2009-09-08
........\m1.m,304,2009-09-04
........\m10.m,1031,2009-09-21
........\m11.m,734,2009-09-19
........\m12.m,546,2009-09-10
........\m13.m,293,2009-10-14
........\m2.m,207,2009-09-04
........\m7.m,1367,2009-10-16
........\m77.m,553,2009-09-20
........\m89.m,542,2009-09-27
........\nlp2.m,731,2009-10-10
........\nlp3.m,741,2009-10-09
........\nlp4.m,590,2009-10-09
........\sp.m,1730,2009-10-14
........\sp2.m,1773,2009-10-11
........\stftsp.m,687,2009-10-12

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xinhaochuli
信号处理小波分析 1)计算信号的小波变换。 2)求出模极大曲线。 3)计算其中两个奇异点的Lipschitz指数。 (Signal processing wavelet analysis 1) the calculation of wavelet transform signals. 2) calculated curve of modulus maxima. 3) the calculation of which two singular points of Lipschitz index.)

2021-01-29 12:58:40下载

积分：1
Autocorrelation
编写MATLAB程序，产生协方差函数为C(τ)=9??^(?10|??| )的零均值平稳高斯过程，产生一条样本函数.测量所产生样本的时间自相关函数，将结果与理论值比较。(Procedures for the preparation of MATLAB produced C covariance function (tau) =9^ (- 10||) zero mean stationary Gauss process to produce a sample function. Measuring the resulting sample time autocorrelation function, the results will be compared with the theoretical value.)

2021-04-08 13:19:01下载

积分：1
ConstructWaveBaseFunction
说明：紧支撑小波基的构造。以Daubechies小波滤波器系数为例，推导出小波函数及尺度函数，并画出其图像. void Convolution(double* pShortData, int nShort, double* pLongData, int nLong) int CalcScaleFunction(double* pOutData) int CalcWaveletFunction(double* pOutData) Convolution()不是通用的离散卷积代码，而是简单地实现了后面两个函数需要的离散卷积，它要求输入的前一个数组长度小于后一数组长度，而且卷积结果就直接覆盖存储在后一数组中。CalcScaleFunction()计算尺度函数，CalcWaveletFunction()计算小波函数。 (Compactly supported wavelet bases constructed. To Daubechies wavelet filter coefficients as an example, the derived wavelet function and scaling function, and draw their images. Void Convolution (double* pShortData, int nShort, double* pLongData, int nLong) int CalcScaleFunction (double* pOutData) int CalcWaveletFunction ( double* pOutData) Convolution () instead of generic discrete convolution code, but simply the realization of a function behind the need for two discrete convolution, which requires input before an array length is less than the array length of the latter, but the result of convolution directly covered by the latter is stored in the array. CalcScaleFunction () calculated scaling function, CalcWaveletFunction () calculation of wavelet function.)

2020-11-10 20:19:45下载

积分：1
Gaborfeature
基于gabor小波变换的论文，对做人脸识别很有用(Gabor wavelet transform-based papers, do face recognition is useful)

2013-02-26 20:18:31下载

积分：1
DirFilter-test_pic
简单的方向滤波器，带测试图的，可以直接运行(Simple directional filter, with a test chart, you can directly run)

2012-09-11 19:46:21下载

积分：1
漫画傅里叶解析-涉谷道雄
说明：介绍傅立叶变换的漫画，不是大量公式叙述或证明，简洁生动，易于理解。(The caricature that introduces Fourier transform, is not a lot of formula narration or proof, concise and vivid, easy to understand.)

2020-06-22 17:00:02下载

积分：1
202
1、求冲激函数、阶跃函数及三角函数的小波变换 2、模极大值曲线 3、求它们的李氏指数(one, seeking impulse function, step function and trigonometry two wavelet transform, modulus maxima curve 3, Lee seeking their index)

2007-03-13 11:29:45下载

积分：1
WAVELET_JX
单分量仿真信号进行小波变换后，小波脊线的提取(After the simulation of a single component signal wavelet transform, wavelet ridge extraction)

2021-04-15 16:58:54下载

积分：1
3D
说明：真正的3 d双树离散小波变换(DWT)的一个数据集x是使用四个严格采样实现可分3 d DWTs在平行。然后subbands四DWTs结合适当。 (The real the 3 d Doubletree discrete wavelet transform (DWT) data set x four to strict sampling separable 3 d the DWTs In parallel. The then the subbands four DWTs combined appropriately.)

2013-04-16 19:35:55下载

积分：1
BCS-SPL-1.5-new
Block-based random image sampling is coupled with a projectiondriven compressed-sensing recovery that encourages sparsity in the domain of directional transforms simultaneously with a smooth reconstructed image. Both contourlets as well as complex-valued dual-tree wavelets are considered for their highly directional representation, while bivariate shrinkage is adapted to their multiscale decomposition structure to provide the requisite sparsity constraint. Smoothing is achieved via a Wiener filter incorporated into iterative projected Landweber compressed-sensing recovery, yielding fast reconstruction. The proposed approach yields images with quality that matches or exceeds that produced by a popular, yet computationally expensive, technique which minimizes total variation. Additionally, reconstruction quality is substantially superior to that from several prominent pursuits-based algorithms that do not include any smoothing

2020-11-23 19:29:34下载

积分：1

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