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Comp_SVD
Image compression using SVD is a very useful compression algorithm. The image size will not decrease in the compression algorithm.
- 2013-10-17 22:31:15下载
- 积分:1
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MATLAB
数值分析,上机题目,求解方程组十分方便
数值分析,高斯公式, 求解方程组十分方便(Numerical analysis, the machine topic is very convenient for solving equations numerical analysis, Gaussian formula is very convenient for solving equations)
- 2008-12-29 13:14:40下载
- 积分:1
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vcPP--renshutongji
人数统计 vc++ 因为 本人需要matlab的人数统计源程序代码 所有先上传自己有的vc++源代码来让大家参考(Number of vc++ because I need matlab source code for all the statistics the number of first upload your own and some vc++ source code to make your reference)
- 2011-04-21 09:34:23下载
- 积分:1
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example5_3
超外差接收机的matalab功能模块仿真,调幅中波收音机的接收頻率段为550KHz 到605KHz,中频为465KHz (The matalab specialized superheterodyne receivers function modules simulation, am medium-wave radio shows for 550 KHz to receive 605 KHz, intermediate frequency for 465 KHz
)
- 2012-01-03 21:34:16下载
- 积分:1
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第3、4讲- Matlab图像处理工具箱及基本函数
说明: 适合新手的matlab教程,方便新手学习了解matlab的基础知识。(The matlab tutorial suitable for novices is convenient for novices to learn and understand the basic knowledge of matlab.)
- 2020-04-29 13:20:22下载
- 积分:1
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face-detection
一个用神经网络进行人脸检测的程序,解压后运行main.m文件,之后对神经网络进行训练,需要一定的时间,耐心等待,最大400个周期,然后就可以对灰度人脸图像进行检测了。
(A neural network with a face detection program, run the main.m file after decompression, the neural network after training, take time, patience, maximum 400 cycles, and then you can on the gray face image detected.)
- 2011-06-03 17:03:04下载
- 积分:1
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SpreadSpectrumPrinciple_Matlab
进行了基本的扩频中的 低检测、电器性检查、分集、瑞丽衰落等等的仿真
运行过(the basic spreading the low detection, electrical inspection, diversity, Ruili decline, and so on the simulation run-off )
- 2007-06-10 14:26:20下载
- 积分:1
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GPSR_6.0
压缩感知中一种非常典型的梯度投影算法,算法的速度非常快(Compressed sensing in a very typical gradient projection algorithm, the algorithm is very fast)
- 2011-04-27 09:56:35下载
- 积分:1
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eemizer_v1.0
再用平行因子分析三维荧光数据时,能够自动调整为最优的条件(automatically determine the appropriate PARAFAC model for EEM data)
- 2011-05-28 21:30:34下载
- 积分:1
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tracking
Tracking of visual phenomena is hard. Very, very hard. And frustrating. You should try not to get discouraged by poor tracking results, but rather concentrate on the specific reasons why your tracker may not be performing well. Is the bad performance predictable from the theoretical properties of the tracker? If so, that s a valuable observation that will serve you well in the future
- 2013-07-24 12:49:21下载
- 积分:1