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pwminverter_fed_im
This program has been written using Matlab/Simulink software. It can be used to find out the behavior of the induction motor behaviore when fed from a PWM inverter. The program is written so that the user can simulate any induction motor he wants by just loading the electrical and the machanical parameters in the workspace. The induction motor is modelled by the 7th order dq model which takes the iron loss component into account. The motor works in open loop but the closed loop can be easly performed by just adding the vector controller or any other controller and a PI speed controller.
- 2011-09-21 16:08:53下载
- 积分:1
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ff
Running a function on several files in Matlab
- 2013-10-22 18:22:05下载
- 积分:1
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datafusion1122
卡尔曼滤波方法解决雷达数据融合问题,本程序针对同步融合。还附有红外数据融合(Asynchronism_Radar.Asynchronism_IR.)
- 2009-06-16 16:20:47下载
- 积分:1
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OSTBC
This is a matlab code for OSTBC transmitter and receiver
- 2015-02-11 03:48:48下载
- 积分:1
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package_emd
需重点研究的关键问题med的快速分解hht的(emd)
- 2010-05-26 12:41:30下载
- 积分:1
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matlab4
利用matlab进行五点三次法平滑处理(时域和频域)(Using matlab 5.3 times France smoothing process (time domain and frequency domain))
- 2013-09-15 10:46:29下载
- 积分:1
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matlab
一个模糊控制程序,实现PID控制~!相信一定能用到的!~(A fuzzy control process to realize PID control ~!)
- 2012-04-24 15:26:07下载
- 积分:1
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fuzzy3
Brain MR Image segmentation using k-means clustering
- 2012-08-13 22:49:34下载
- 积分:1
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ShortestPath2Dijkstra
最短路dijkstra问题,简单易懂的matlab程序(Most short-circuit the dijkstra problems, and to understand the matlab program)
- 2012-08-19 11:37:14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