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vdpsl

于 2013-07-31 发布文件大小:8KB

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This is a simulation of a nonlinear second order system.

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Elements-de-MATLAB
Matlab est un langage simple et très efficace, optimisé pour le traitement des matrices, d’où son nom. Pour le calcul numérique, Matlab est beaucoup plus concis que les “vieux” langages (C, Pascal, Fortran, Basic). Un exemple: plus besoin de programmer des boucles modifier pour un à un les éléments d’une matrice. On peut traiter la matrice comme une simple variable. Matlab contient également une interface graphique puissante, ainsi qu’une grande variété d’algorithmes scientifiques.

2011-05-07 01:47:28下载

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2011-06-19 21:34:20下载

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2011-11-17 19:39:01下载

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Radon transform and inverse radon , and their histogram step by step. can be use for edge detection and finding the number of object in image

2013-12-11 16:16:11下载

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2021-01-03 16:58:56下载

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Matlab讲义高级第4章，大家分享一下(Matlab senior notes, Chapter 4, we share)

2008-01-01 13:46:22下载

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matlab
数字控制系统仿真与综合应用：设控制对象为 W1=10/s(1+0.1s)(1+0.05s),采样周期T=0.2s。（1）采用零阶保持器，将W1(s)转换成W1(z),串接一个计算机调节模型D(z)组成一个典型的数字反馈系统。分别用仿真方法得到系统在单位阶跃输入作用下的响应和系统在单位速度输入时的输出响应。 (Digital control system simulation and comprehensive application: set control object for W1 = 10/s (1+ 0.1 s) (1+ 0.05 s), the sampling period T = 0.2 s. (1) the zero order keep device, will W1 (s) convert W1 (z), the combination of a computer adjusting model D (z) composed of a typical digital feedback system. The simulation method were used to get in the unit step input system under the action of response and system in the unit of output response speed input. )

2012-04-19 14:38:25下载

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StepclassV2
逐步判别分析的主函数用于分类 [sel,c,c0,re,P]=StepclaassV2(data,[50 50 50],data,10) 输入变量 x为训练集.每行为一个样本，每列为一个变量. Class_x,为训练集的分类情况，一行，为各类样本数量,例如[5 6 9] Test为待分类样本. 输出变量：sel为选择的变量序号，c,c0为拟合出的判别函数.re为对Test的判别结果,P为其后验概率. author 王新 2012.4.8 例子Sample: load fisheriris x=meas Class_x=[50,50,50] Test=meas(1:5,:) Fa1=4 [sel,c,c0,re,P]=StepclaassV2(x,Class_x,Test,Fa1)( Stepwise discriminant analysis for the classification of the main function [sel, c, c0, re, P] = StepclaassV2 (data, [50 50 50], data, 10) input variables x as the training set, each conduct a sample of each as a variable. Class_x, the classification for the training set, a row, the number of samples for all types, for example, [5 6 9] Test sample to be classified. output variable: sel for the selected variables serial number, c, c0 is fitted discriminant function. re discrimination results for the Test, P its posterior probability. author Wang 2012.4.8 examples Sample: load fisheriris x = meas Class_x = [50,50,50] Test = meas (1:5, :) Fa1 = 4 [sel, c, c0, re, P] = StepclaassV2 (x, Class_x, Test, Fa1))

2020-09-18 12:27:56下载

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raoguosuoyouyonghudecengHOOK
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2014-01-03 06:25:48下载

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