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pca
主成分分析法(pca)在matlab上的实现(pca in matlab)
- 2010-06-28 13:15:22下载
- 积分:1
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Autoencoder_Code
Autoencoders for dimensionality reduction using stacked restricted boltzmann machines
- 2014-08-07 00:01:08下载
- 积分:1
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c13
CIC滤波器的插值运算,并可以实现数字下变频的整个算法的研究,与仿真(design and simulink )
- 2012-03-31 17:35:32下载
- 积分:1
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DBF
详细讲述了阵列信号处理中的数字波束合成算法(This ppt explain the array signal processing in digital beamforming algorithm in detail。)
- 2011-12-02 01:46:59下载
- 积分:1
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BaiTH2
Detectec Detectec Detectec Detectec Detectec Detectec Detectec Detectec Detectec Detectec Detectec Detectec Detectec Detectec
- 2013-11-13 06:30:12下载
- 积分:1
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M文件
说明: 相量测量工具的优化配置,相量测量装置的功能,向量测量装置的用途(Optimal pmu Placement)
- 2020-04-15 21:05:21下载
- 积分:1
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RIV
适当选择辅助变量,使之满足相应条件,参数估计值就可以是无偏一致。估计辅助变量法的计算量与最小二乘法相当,但辨识效果却比最小二乘法好的多。尤其当噪声是有色的,而噪声的模型结构又不好确定时,增广最小二乘法和广义最小二乘法一般都不好直接应用,因为他们需要选用特定的模型结构,而辅助变量法不需要确定噪声的模型结构,因此辅助变量法就显得更为灵活,但辅助变量法不能同时获得噪声模型的参数估计。(Choose appropriate secondary variables, meet the relevant conditions and parameter estimate can be unbiased consistent. Estimated auxiliary variable method calculation and least square method is quite, but the identification effect is much better than the least square method. Especially when the noise is colored, and noise model structure and not sure, augmented the least squares and the generalized least squares method is generally not used directly, because they need to choose specific model structure, and auxiliary variable method does not need to make sure that noise model structure, so the auxiliary variable method is more agile, but not at the same time auxiliary variable method for noise model parameter estimation.)
- 2012-12-28 16:06:51下载
- 积分:1
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COM
精通MATLAB与C和C++混合程序设计第一章(Proficient in MATLAB and C and C++ hybrid program)
- 2012-04-12 15:39:17下载
- 积分:1
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SIFT_YantaoNoemie
基于matlab实现SIFT算法,好用!!(Based on matlab realize SIFT, easy to use! !)
- 2013-10-06 20:15:14下载
- 积分:1
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1
matlab使用垂直Sobel算子,自动选择阈值
[VSFAT Threshold]=edge(f, sobel , vertical )
边缘探测
figure,imshow(f),title( 原始图像 ),
显示原始图像
figure,imshow(VSFAT),title( 垂直图像边缘检测 )
显示边缘探测图像
使用水平和垂直Sobel算子,自动选择阈值
SFST=edge(f, sobel ,2)
figure,imshow(SFST),title( 水平和垂直图像边缘检测 )
显示边缘探测图像
使用指定45度角
Sobel算子滤波器,指定阈值
s45=[-2 -1 0 -1 0 1 0 1 2]
SFST45=imfilter(f,s45, replicate )
SFST45=SFST45>=2
figure,imshow(SFST45),title( 45度角图像边缘检测 )
显示边缘探测图像
(matlab I=rgb2gray(I0)
J0=double(I) [VSFAT Threshold]=edge(f, sobel , vertical ) figure,imshow(f),title figure,imshow(VSFAT),title)
- 2013-12-18 15:42:14下载
- 积分:1