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Kalman-filtering
kalman滤波方面的书籍,是一本经典的书籍。详细讲述了各种方法及组合滤波方法(kalman filter books, is a classic book. Detail the various methods and composition of the filter)
- 2010-12-23 19:47:24下载
- 积分:1
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13
说明: 图象压缩方面的论文pdf格式
可用于毕业设计方面的工作(Image compression pdf format papers for school design work)
- 2010-05-26 20:37:18下载
- 积分:1
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LFM
该程序可以用于产生LFM信号,并输出在理想和加噪情况下分别经过匹配滤波器后的结果。(The program can be used to generate LFM signal, and outputs the noise in the ideal case and processing each of the results after the matched filter.)
- 2013-12-14 15:56:00下载
- 积分:1
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matifus
一个用于图像融合的matlab源程序,可以用matlab仿真(A source image fusion matlab, matlab simulation can be used)
- 2009-05-19 18:57:05下载
- 积分:1
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pca-cPP-svd-algorithm
主成分分析的c++实现使用奇异值分解svd算法(Principal Component Analysis based on svd algorithm ,used c++)
- 2012-11-22 15:18:38下载
- 积分:1
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fb203b56d21a
matlab gui很好的例子,对学习有很大帮助。(matlab gui good example of great help in learning.)
- 2011-05-24 04:35:27下载
- 积分:1
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bipso
围绕粒子群的当前质心对粒子群重新初始化.这样,每个粒子在随后的迭代中将在新的位置带着粒子在上次搜索中获得的“运动惯性”(wvi)向Pi,Pg的方向前进,从而可以在粒子群的运动过程中获得新的位置,增加求得更优解的机会.随着迭代的继续,经过变异的粒子群又将趋向于同一点,当粒子群收敛到一定程度时又进行下一次变异,如此反复,直到迭代结束.(particle swarm around the center of mass of the current PSO reinitialization. Thus, Each particle in the next iteration will be in the new location with particles in the last search was the "inertia" (wvi ) Pi, Pg orientation, and thus can PSO course of the campaign was a new position, increase seek better solutions opportunities. With the continued iteration, after variation of PSO will tend to the same point. When PSO converge to a certain extent when the next variation, so repeatedly, until the end of iteration.)
- 2006-08-19 17:39:33下载
- 积分:1
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Process-Control
多火电厂主汽温度控制系统的过程控制进行仿真(Of the thermal power plant main steam temperature control system process control simulation
)
- 2011-07-09 21:57:08下载
- 积分:1
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small_image
MATLAB实现的高光谱图像的端元提取,可以自己下载高光谱图像,然后修改下程序就能用了。(MATLAB implementation of hyperspectral image endmember extraction of hyperspectral images can download and modify the following program can be used.)
- 2021-04-19 20:58:51下载
- 积分:1
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ChildFrm
The first scheme is based on the spatial locality of feature vectors corresponding
to similar images. Learning is effected by modifying the query vector to incorporate the
positive examples. The second scheme is based on “distorting” our view of the feature space. An
new similarity distance between an image and the query is learned from the relevance feedback.
- 2009-11-23 06:51:13下载
- 积分:1