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HttpAbstractParamBean
This AttributeVisitor marks all methods that catch exceptions.
- 2013-12-02 13:42:27下载
- 积分：1
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errorbar_groups
matlab code for Grouped bar plots with error bars
- 2015-02-03 14:33:26下载
- 积分：1
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hmt.m
小波域的树模型去噪采用ＥＭ算法训练模型参数由Ｍatlab编程实现仿真(Wavelet denoising tree model using EM algorithm training model parameters from Matlab Simulation Programming)
- 2007-05-16 16:28:11下载
- 积分：1
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MTurkThesis07-2008
A Homography-Based Multiple-Camera Person-Tracking
- 2009-03-26 14:38:42下载
- 积分：1
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askd
amplitude shift keying
- 2009-12-01 17:05:56下载
- 积分：1
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code
Matlab based Static Simulator, from Laiho s book for UMTS
- 2009-06-02 22:40:30下载
- 积分：1
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wavelet_speechenhancing
说明小波消噪的理论，阈值估算和提取，给出在MATLAB下阈值估算和消噪的函数，并在语音信号处理中增强语音。(Explain the theory of wavelet denoising, threshold estimation and extraction, are given in the MATLAB under the threshold estimation and de-noising function, and speech signal processing to enhance voice.)
- 2008-08-12 08:21:08下载
- 积分：1
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panel_28_08_2010_02
panel plot toolbox for subplots
- 2011-08-27 03:47:50下载
- 积分：1
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nebulous_logic
example of nebulous logic
- 2013-08-29 05:20:32下载
- 积分：1
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fs_sup_relieff
Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重：
如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules:
If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)
- 2018-04-17 14:41:55下载
- 积分：1
