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hyperChaos
求离散超混沌系统的自相关和互相关函数，本程序使用的是kawakami超混沌系统(for discrete hyperchaotic system autocorrelation and cross-correlation function, This procedure is used in super-chaotic system kawakami)
- 2006-09-21 11:30:56下载
- 积分：1
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clipping
实现用matlab仿真OFDM系统限幅（clipping）法抑制峰均比的原理(Achieve PAPR of OFDM system simulation using matlab clipping (clipping) Act Principles)
- 2014-03-02 11:26:25下载
- 积分：1
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SFIC_modified
说明： 结合SIC修改的SFIC,其中利用SIC的因果和非因果的思想。(SFIC modified according to someway of SIC)
- 2011-03-17 09:54:01下载
- 积分：1
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PAST_MUSIC
past-music算法，用来进行谐波分量的求解。速度快，效果佳(past-music algorithm used for solving the harmonic components. Fast, good effect)
- 2010-05-07 14:37:16下载
- 积分：1
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JM97Bcount
97年中国大学生数学建模竞赛B题（枚举法） (1997 China Undergraduate Mathematical Contest in Modeling B (enumeration))
- 2013-07-16 21:42:28下载
- 积分：1
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sobel
自编边缘提取方法，能够准确的提取边缘，编写简单。(Self-edge detection method, able to accurately extract the edge, simple to prepare.)
- 2008-04-22 09:52:15下载
- 积分：1
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kks
Kreftwerk-Kennzeichen system
Identification System for Power Station
- 2014-09-01 15:14:55下载
- 积分：1
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session34
经济学的数值方法 非线性优化。涉及Broyden s Method Powell s Hybrid Method,定价问题(Broyden s Method Powell s Hybrid Method，pricing set)
- 2014-01-15 14:43:22下载
- 积分：1
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shibie
基于奇异值分解的人脸识别方法
梁毅雄 龚卫国 潘英俊 李伟红 刘嘉敏 张红梅
提出了一种将傅里叶变换和奇异值分解相结合的人脸自动识别方法.首先对人脸图像进行傅里叶变换,得到其具有位移不变特性的振幅谱表征.其次,从所有训练图像样本的振幅谱表征中给定标准脸并对其进行奇异值分解,求出标准特征矩阵,再将人脸的振幅谱表征投影到标准特征矩阵后得到的投影系数作为该人脸的模式特征.然后,对经典的最近邻分类器算法进行了改进,并采用模式特征之间的欧式距离作为相似性度量,从而完成对未知人脸的识别.采用ORL (Olivetti Research Laboratory)人脸库对本文提出的人脸识别方法进行验证,获得了100.00 的识别率.实验结果表明,本方法优于现有的基于奇异值分解的人脸识别方法,且对表情、姿态变换等具有一定的鲁棒性.
(Face recognition based on singular value decomposition method
Deliberate simultaneously Gong Weiguo Li Wei Hung Stephen Lau, Hong-Mei Zhang Ying-Jun Pan
Paper, a Fourier transform and singular value decomposition of the combination of automatic face recognition. First of all, the face image by Fourier transformation, it has the same characteristics of the displacement amplitude spectra. Secondly, all training The amplitude spectrum of the sample images given in standard face representation and its singular value decomposition, find the standard characteristic matrix, then the amplitude of spectral characterization of human faces projected onto the standard characteristic matrix of projection coefficients obtained as the face of the model features . Then, the classical nearest neighbor classifier is improved, and the use of Euclidean distance between pattern features as the similarity measure, thus completing the identification of unknown human faces. using ORL (Olivetti Research La)
- 2010-05-17 14:29:31下载
- 积分：1
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jacobi
perform Jacobi method iterations
- 2012-04-26 15:30:35下载
- 积分：1
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