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xiefangcha
高频雷达 目标检测 去除Bragg峰 采用现代信号处理的方法 协方差方法(Remove high-frequency radar target detection Bragg peak using the methods of modern signal processing methods covariance)
- 2011-01-30 11:03:05下载
- 积分：1
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gmm3.m
高斯混合模型的核心计算方法，matlab里可直接调用(Core calculation method based on Gaussian mixture model, matlab years can be called directly)
- 2014-10-04 12:55:08下载
- 积分：1
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生成反射系数
生成反射系数的，希望对大家有帮助,是我们实验室用做地震资料处理流程中合成地震反射系数用的，具体看程序就知道。(you can see chinese explane,)
- 2020-07-07 17:18:57下载
- 积分：1
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pulseblanking
实现脉冲消隐以在通信系统去除较大干扰,保证误码率性能(Realization of pulse blanking to remove larger interference in communication system, guaranting the bit error rate performance)
- 2014-02-19 10:41:15下载
- 积分：1
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elliptic_mesh
椭圆型方程生成网格。简单方便使用，生成网格正交(Elliptic Equations mesh generation. Simple and easy to use, generate orthogonal grid)
- 2021-04-19 17:58:51下载
- 积分：1
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K_average
K_average聚类分析程序，包含多个子文件，适用于模式识别和聚类分析(K_average)
- 2009-04-16 21:13:28下载
- 积分：1
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lte-eea3-eia3-zuc-decry
LTE eea3 eia3 zuc等算法的详尽描述，其中包含有实现源码，测试例。均来自标准文档。
(A detailed description of LTE eea3 eia3 zuc algorithm, which includes the source code, test cases. From the standard document.)
- 2014-08-18 10:47:30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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paper2
An Efficient Inter Carrier Interference Cancellation Schemes for OFDM Systems
- 2015-03-22 00:48:08下载
- 积分：1
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vlctableGen
CAVLC tables generator
- 2010-06-24 19:08:40下载
- 积分：1
