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optimum.rar
基于遗传算法整定的PID控制算法的Matlab仿真源程序(Based on genetic algorithm-tuning PID control algorithm of the Matlab simulation source)
- 2008-07-06 21:17:34下载
- 积分：1
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zoomfft
该程序是我把上面的Matlab版 ZoomFFT改写成Vc++版,该程序通过编译没有问题,我调用函数(The program is my Matlab version of the above into ZoomFFT rewritten Vc++ version of the program through the compiler there is no problem, I call the function)
- 2009-06-30 22:43:32下载
- 积分：1
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coooode
documentd:My DocumentsDownloads
- 2011-12-09 22:02:57下载
- 积分：1
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ch1example3prg1
单摆运动过程的建模和仿真，忽略空气阻力因素(Pendulum movement of the modeling and simulation process, ignore the air resistance factor)
- 2009-04-20 12:47:09下载
- 积分：1
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matlab74543
matlab programmer plc
- 2012-04-16 08:53:55下载
- 积分：1
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shuzi
基带信号周期采样的分析与仿真设计低通信号，对该信号进行周期采样，最后从采样数据中恢复原始信号；改变采样频率，给出相应的仿真结果；考察前端抗混叠滤波器的作用和必要性；分析后端理想恢复滤波器是否唯一。(
Periodic sampling of the baseband signal analysis and simulation to design low pass signal, the signal is periodic sampling, finally recover the original signal from the sampled data changing the sampling frequency, gives the corresponding simulation results examine the front of the role of anti-aliasing filter and necessity analysis backend ideal restoration filter is unique.)
- 2013-11-23 15:46:45下载
- 积分：1
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Matlab-GUI-Filter
this code provide for using matlab GUI filter
- 2010-01-01 14:25:04下载
- 积分：1
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Rate-3_4
LDPC encoding and decoding of rate 4/7
- 2014-09-09 19:57:14下载
- 积分：1
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121
DSP course lectures lab
- 2011-11-07 23:51:22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
