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Matlab-UsingSimulink
Matlab basic ebook. It usful to get started with it.
- 2010-08-31 20:22:24下载
- 积分：1
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F74966214_1
说明： 在cmd介面實做出老鼠走迷宮，可從迷宮逃出(In the cmd interface really make a mouse Maze, escaped from the Maze)
- 2010-03-28 16:09:42下载
- 积分：1
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MATLABprogrammingCH09
這是一本MATLAB程式設計延伸技巧程式書本上的程式碼CH9(一次無法全部上傳會斷線)(This is an extension of MATLAB programming skills in program code books CH9)
- 2010-05-27 14:31:13下载
- 积分：1
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IIR-filter-design
基于matlab的IIR滤波器设计，程序简单易懂(Matlab-based IIR filter design procedures are simple)
- 2013-11-04 21:07:16下载
- 积分：1
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navieBayes
在matlab环境下的一个朴素贝叶斯分类器，大家可以参考下(Matlab environment a Naive Bayes classifier, we can refer to the following)
- 2012-10-23 10:57:17下载
- 积分：1
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Kalman
此程序相关卡尔曼滤波，用matlab描述了卡尔曼滤波的过程。(ocedure-related Kalman filtering, Kalman filtering with matlab describes the process.)
- 2011-12-20 16:31:18下载
- 积分：1
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cc1_matlab-
说明： 一些关于信道编译码的Matlab源代码,国外一所大学的matlab编译码解答。(some of the channel codec Matlab source code, a foreign university Matlab encryption answer.)
- 2006-04-07 15:14:03下载
- 积分：1
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mallat
说明： 用mallat分解与重构算法实现一维信号的分解和重构(Mallat decomposition and reconstruction algorithm used to achieve one-dimensional signal decomposition and reconstruction)
- 2010-04-29 15:23:04下载
- 积分：1
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Interferece-Alignment
throughout with interference alignment
- 2020-10-27 23:29:58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
