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classifier2
Classifier pdf.
Its can be used to learn what is classifier, hoe it can be applied to images.
- 2011-02-15 18:47:18下载
- 积分:1
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pca
说明: 基本pcs算法,可以实现PCA算法,看负荷得分(Basic pcs algorithm)
- 2011-03-19 11:17:50下载
- 积分:1
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BERforMIMO
BER plot in rayleigh channel with maximal ratio combining technique for MIMO
- 2010-10-08 14:26:50下载
- 积分:1
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control-deg
This is control design and simulation document of PMSM. Hope you can edit and use it to your exercise. It is not actually integrated but I think it will be useful for you.
- 2013-11-07 23:16:33下载
- 积分:1
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Documentation
some matlab codes for image processing
- 2009-06-02 15:50:09下载
- 积分:1
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GM11
GM11适应范围.PDF文件;非常实用的GM11模型Matlab程序。C语言基础即可明白,无需多言(GM11 adaptation range. PDF file very useful GM11 model Matlab procedures. C programming language to understand, no need to say)
- 2013-10-22 11:26:49下载
- 积分:1
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fourieroptics
傅里叶光学仿真,可模拟各种平顶高斯光束并对其参数进行设置。(Fourier optics simulation, can simulate a variety of flattened Gaussian beam and its parameters.)
- 2013-12-27 02:04:07下载
- 积分:1
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ZCR
autocov computes the autocovariance between two column vectors X and Y with same length N using the Fast Fourier Transform algorithm from 0 to N-2.
The resulting autocovariance column vector acv is given by the formula:
acv(p,1) = 1/(N-p) * sum_{i=1}^{N}(X_{i} - X_bar) * (Y_{i+p} - Y_bar)
where X_bar and Y_bar are the mean estimates:
X_bar = 1/N * sum_{i=1}^{N} X_{i} Y_bar = 1/N * sum_{i=1}^{N} Y_{i}
It satisfies the following identities:
1. variance consistency: if acv = autocov(X,X), then acv(1,1) = var(X)
2. covariance consistence: if acv = autocov(X,Y), then acv(1,1) = cov(X,Y)
- 2013-05-26 22:12:50下载
- 积分:1
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base-paper2
Abstract—A novel algorithm to remove rain or snow streaks
a video sequence using temporal correlation and low-rank
matrix completion is proposed in this paper. Based on the
observation that rain streaks are too small and move too fast
to affect the optical flow estimation between consecutive frames,
we obtain an initial rain map by subtracting temporally warped
frames a current frame. Then, we decompose the initial
rain map into basis vectors based on the sparse representation,
and classify those basis vectors into rain streak ones and outliers
with a support vector machine. We then refine the rain map
by excluding the outliers. Finally, we remove the detected rain
streaks by employing a low-rank matrix completion technique.
Furthermore, we extend the proposed algorithm to stereo video
deraining. Experimental results demonstrate that the proposed
algorithm detects and removes rain or snow streaks efficiently,
outperforming conventional algorithms.
- 2015-07-21 11:46:13下载
- 积分:1
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Gsapvitessevariable2
la machine gsap avec vitesse var
- 2019-04-21 19:13:40下载
- 积分:1