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ICAforImageProcessing
用Matlab实现的用于图像处理的独立分量分析算法(Realize using Matlab for image processing algorithm for independent component analysis)
- 2007-09-25 13:28:39下载
- 积分：1
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Wiener111111
说明： 维纳滤波器，在matlab中运行，此为记事本文件，复制到matlab中M文件即可运行(Wiener filter in matlab run, this is Notepad file, copy it to matlab file to run in the M)
- 2008-11-20 09:38:14下载
- 积分：1
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knnPcaWithGA
In this code I have used GA in supervised PCA to find the best coeficients for overall covariance. the classification is made by KNN
- 2010-05-07 01:09:01下载
- 积分：1
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simulationOfLFMRadar
对线性调频脉冲压缩雷达进行了仿真，考虑了实际目标回波包含的系统噪声和地物杂波、高频放大器设计、混频器设计、中频放大器设计、正交鉴相器设计、时域和频域脉冲压缩(脉压)、MTI、MTD及CFAR恒虚警等多个方面。(This code simulates the system of LFM pulse compression radar taking into account of system noise and clutter contained in object signal and many other aspects important in a complete radar system.)
- 2020-10-26 20:29:59下载
- 积分：1
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TouYing
实现图像中文字定位功能，特别是新闻图像中的标题字幕的定位，算法简单，效果也不错(Text positioning of image, especially the image of the title locate news captions, the algorithm is simple, with good results)
- 2015-03-26 15:55:46下载
- 积分：1
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mpiPopenmp
采用MPI+OpenMP混合模型设计并实现光化学反应双层并行模拟算法，上层基于MPI实现节点间的原子分解并行,下层基于OpenMP实现节点内的多线程矩阵并行乘法。(With MPI+OpenMP mixed model was designed and implemented The photochemical reaction bunk parallel simulation algorithms, the upper atomic decomposition based on inter-node MPI implementations parallel, the lower based on OpenMP nodes of multithreading matrix parallel multiplication.)
- 2012-11-28 16:56:50下载
- 积分：1
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dct-with-noise
it is a file to watermark the image file in matlab
- 2011-01-18 14:44:36下载
- 积分：1
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HOG
shape feature extraction of Histogram of Gradient
- 2011-11-29 15:28:51下载
- 积分：1
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rough
matlab粗糙集课件,共六讲，讲解matlab下如何使用rough sets(matlab rough set courseware, a total of six speakers to explain how to use rough sets under matlab)
- 2009-11-12 15:17:02下载
- 积分：1
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LIBRA_19jun09
Our toolbox currently contains implementations of robust methods for
location and scale estimation, covariance estimation (FAST-MCD), regression (FAST-
LTS, MCD-regression), principal component analysis (RAPCA, ROBPCA), princi-
pal component regression (RPCR), partial least squares (RSIMPLS) and classi¯ cation
(RDA). Only a few of these methods will be highlighted in this paper. The toolbox
also provides many graphical tools to detect and classify the outliers. The use of these
features will be explained and demonstrated through the analysis of some real data
sets.
- 2009-06-25 09:39:04下载
- 积分：1
