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matlab
matlab下的数字图象处理例程,其中有关图片文件只要随便找个图片就可以了(matlab under the digital image processing routines, including the relevant picture file as long as you can not find a picture of the)
- 2007-11-06 21:38:49下载
- 积分：1
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MATLAB
通信系统仿真原理与无线应用 源代码 大家如有需要可以下载看看(Principles of Communication Systems Simulation with Wireless Applications source code)
- 2009-06-26 10:01:27下载
- 积分：1
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2
说明： Copula函数，以及相关性计算和相应的散点图(Copula compute)
- 2013-11-18 22:52:38下载
- 积分：1
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MUSIC-Algorithm-for-document
这是关于MUSIC算法的文档。希望对初学空间谱估计的人有帮助！(This is the document of MUSIC algorithm. I hope it can help beginners of spatial spectrum estimation.
)
- 2014-02-16 18:17:39下载
- 积分：1
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LSBembed
用MATLAB编写的 LSB 信息隐藏软件(MATLAB LSB prepared by the Software Information Hiding)
- 2006-11-16 19:10:39下载
- 积分：1
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nakagami
说明： Nakagami-m分布能用来对比瑞利分布条件更苛刻的衰落信道进行建模，最适合于郊区无线多径信道上接受的数据信号，瑞利分布是它 时的特例。(Nakagami-m distribution can be used to model fading channels with more stringent Rayleigh distribution conditions. It is most suitable for data signals received on suburban wireless multipath channels. Rayleigh distribution is its special case.)
- 2020-03-10 15:35:40下载
- 积分：1
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gm2trellis
This program is used to compute stbc using trelis code
- 2010-12-13 17:43:31下载
- 积分：1
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zhuiganfa-LU
追赶法和LU（coolittle） 算法源程序。。。(coolittle algorithm source code)
- 2011-12-14 21:06:20下载
- 积分：1
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from_VSFM_to_MATLAB
Vsfm to Matlab
by Bashar Alsadik
05 Feb 2014
Vsfm to Matlab
- 2014-02-06 16:24:45下载
- 积分：1
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adaboost
AdaBoost元算法属于boosting系统融合方法中最流行的一种，说白了就是一种串行训练并且最后加权累加的系统融合方法。
具体的流程是：每一个训练样例都赋予相同的权重，并且权重满足归一化，经过第一个分类器分类之后，
计算第一个分类器的权重alpha值，并且更新每一个训练样例的权重，然后再进行第二个分类器的训练，相同的方法.......
直到错误率为0或者达到指定的训练轮数，其中最后预测的标签计算是各系统*alpha的加权和，然后sign（预测值）。
可以看出，训练流程是串行的，并且训练样例的权重是一直在变化的，分错的样本的权重不断加大，正确的样本的权重不断减小。
AdaBoost元算法是boosting中流行的一种，还有其他的系统融合的方法，比如bagging方法以及随机森林。
对于非均衡样本的处理，一般可以通过欠抽样(undersampling)或者过抽样(oversampling)，欠抽样是削减样本的数目，
过抽样是重复的选取某些样本，最好的方法是两种进行结合的方法。
同时可以通过删除离决策边界比较远的样例。
(AdaBoost boosting systems dollar fusion algorithm is the most popular one, it plainly systems integration approach is a serial train and final weighted cumulative.
Specific process is: Each training example is given equal weight, and the weights satisfy normalization, after the first classifiers after
Calculating a first classifier weights alpha value for each sample and updates right weight training, and then the second classifier training, the same way .......
0, or until the specified error rate training rounds, wherein the label is the calculation of the final prediction system* alpha weighted and then sign (predicted value).
As can be seen, the training process is serial, and weight training examples is always changing, the right of the wrong sample weight continued to increase, the right to correct sample weight decreasing.
AdaBoost algorithm is an element, as well as other methods of boosting popular systems integration, such as bagging and random forest method.
For )
- 2014-07-09 19:24:29下载
- 积分：1
