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random_walk
2D version of Brownian motion. A random walk is similar to markov process, however a
markov process has no memory, where a random walk uses an initial state.
The next step in the walk does not necessarily depend on your current
state but will be referenced from your current state, that is to say the
random vector is added to your current state. depending on complexity
- 2013-02-13 05:08:58下载
- 积分：1
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xray_new
Image Reconstruction
- 2013-10-07 03:19:36下载
- 积分：1
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lorenz
lorenzx相位图 吸收引子 混沌 chaos(lorenz system phase)
- 2013-09-22 14:57:10下载
- 积分：1
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Motion-estimation-image-registration
运动估计，图像配准，能应用在视频的超分辨上。(Motion estimation, image registration, can be applied in the super-resolution video.)
- 2015-04-21 10:05:22下载
- 积分：1
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硕士论文 fellow 学生.pdf
felllow 学生 ，无线充电论文，挺好的 ，两篇SCI论文(Felllow student, wireless charging paper, very good, two SCI papers)
- 2018-10-12 15:42:04下载
- 积分：1
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The-simulation-of-OFDM-system
用matlab对OFDM系统进行仿真，并添加高斯白噪声，得到一条BER曲线(Using matlab for OFDM system simulation, and add white Gaussian noise, to obtain a BER curve)
- 2013-09-03 15:40:27下载
- 积分：1
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ImageGallery
ImageGallery extends NoSearchActivity implements for Andriod.
- 2013-12-13 14:50:53下载
- 积分：1
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ooc
正交扩频码ooc的matlab代码。五个用户情况(Orthogonal spreading code of the matlab code for ooc. Five users of)
- 2009-10-21 09:13:24下载
- 积分：1
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shanks
function [a,b,err] = shanks(x,p,q)
SHANKS Model a signal using Shanks method
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Usage: [a,b,err] = shanks(x,p,q)
The sequence x is modeled as the unit sample response of
a filter having a system function of the form
H(z) = B(z)/A(z)
The polynomials B(z) and A(z) are formed from the vectors
b=[b(0), b(1), ... b(q)]
a=[1 , a(1), ... a(p)]
The input q defines the number of zeros in the model
and p defines the number of poles. The modeling error
is returned in err.
- 2012-04-18 09:58:03下载
- 积分：1
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motorsimulink
基于比例趋近率的控制器实现位置跟踪,滑模控制(the position tracking based on proportion approach )
- 2013-10-06 21:10:31下载
- 积分：1
