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C2
说明： s1 is the M-file description of the SIMULINK system named s1.
The block-diagram can be displayed by typing: s1.
SYS=s1(T,X,U,FLAG) returns depending on FLAG certain
system values given time point, T, current state vector, X,
and input vector, U.
FLAG is used to indicate the type of output to be returned in SYS.
- 2010-03-03 17:12:18下载
- 积分：1
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01_introduction
gives introduction about matlab
- 2011-07-20 00:16:41下载
- 积分：1
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kpcaFordata
KPCA故障诊断程序 主要是KPCA进行故障诊断对数据的处理，数据挖掘(KPCA principal component analysis code)
- 2015-02-11 09:41:26下载
- 积分：1
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FH-simulation
By using this matcode codes a simple frequency Hopping system can be simulated. The number of frequencies to be used can be changed by changing the parameters
- 2014-02-20 19:26:34下载
- 积分：1
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QNNPiris
自己写的一个 利用量子神经网络对iris数据进行分类的 matlab例子，希望对大家有用(An application of quantum neural networks to write Matlab examples of iris sort data, I hope useful to everyone)
- 2020-11-11 19:59:45下载
- 积分：1
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ZF_4by4
Wireless communication 4 by 4 mimo linear detection by ZF scheme
- 2015-06-13 23:54:41下载
- 积分：1
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MATLAB-and-SIMULINK
一本工具书，详细介绍了simulink的各个模块。(A book, detailing each module in Simulink.)
- 2012-06-14 09:35:24下载
- 积分：1
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pca
说明： 主成分分析：
(1) 根据指标的属性将原始数据统一趋势化
(2) 利用协方差、相关系数矩阵进行主成分分析，判断可否用第一主成分排名？(Principal component analysis:
(1) Unify and trend the original data according to the attribute of the indicator
(2) Using covariance and correlation coefficient matrix for principal component analysis, can we use the first principal component ranking?)
- 2020-05-18 11:52:07下载
- 积分：1
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tongtai
用同态滤波的方法增强图像对比度，解决因为光照问题引起的图像模糊问题。(By homomorphic filtering method to enhance image contrast, to solve the problem because the light-induced image blurring problem.)
- 2009-05-13 21:19:43下载
- 积分：1
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T-HOMEWORK
用Parzen窗法或者kn近邻法估计概率密度函数，得出贝叶斯分类器，对测试样本进行测试，比较与参数估计基础上得到的分类器和分类性能的差别.2． 同时采用身高和体重数据作为特征，用Fisher线性判别方法求分类器，将该分类器应用到训练和测试样本，考察训练和测试错误情况。将训练样本和求得的决策边界画到图上，同时把以往用Bayes方法求得的分类器也画到图上，比较结果的异同。3．选择上述或以前实验的任意一种方法，用留一法在训练集上估计错误率，与在测试集上得到的错误率进行比较。(Use Parzen Windows method or the kn neighbor method estimated probability density function, draw the bayes classifier, to test sample to test, and the parameter estimation is based on the classifier and get the difference of classification performance. 2. At the same time the height and weight data as the characteristic, with Fisher identification method for linear classifier, and the application of the classifier to training and test sample, investigation and test training error condition. Will the training sample and utility of decision on the drawing boundary paint, and at the same time before the Bayes method with optimal classifier also paint chart, the result of the comparison of the similarities and differences. 3. Select the above or before any a kind of method of experiment, with a method for training set in the estimation error rates, and on the test set get error rates are compared.)
- 2012-04-17 22:59:50下载
- 积分：1
