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Bai6-Nhapxuat
Maple
Bai 6: Nhap xuat
- 2010-11-28 11:59:40下载
- 积分：1
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MATLAB_plot_mesh_etc_examples
MATALB中关于绘图和图像操作的实例,由目录由源程序,很全面.还包括矩阵的基操作和GUI设计等等 .(MATALB on mapping and image manipulation examples, from the directory from the source, to be comprehensive. Also includes the matrix-based operations and GUI design and so on.)
- 2010-02-07 14:49:46下载
- 积分：1
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fuzzer_PID
说明： 基于MATLAB编程模糊控制PID源程序(PID fuzzy control based on MATLAB programming source code)
- 2010-04-12 22:55:35下载
- 积分：1
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mye4
自动获得获得输入的数字的最大公约数最小公倍数(Enter the number of automatic access to the least common multiple greatest common divisor)
- 2010-05-10 19:51:21下载
- 积分：1
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mathematica
mathmatics学习资料,比较实用,亲身感受(mathmatics learning materials, more practical, personal experience)
- 2014-12-03 10:53:28下载
- 积分：1
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Extractedintheimage
利用matlab提取图片中的曲线数据,非常棒，对于写论文很有用(Extracted in the image using matlab curve data, very good, very useful for writing papers)
- 2011-01-17 09:55:53下载
- 积分：1
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CDMA-SYSTEM
CDMA系统仿真 扩频调制级解扩 实现码分多址(CDMA spread spectrum modulation level system simulation realize CDMA despreading)
- 2014-12-20 20:44:04下载
- 积分：1
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chengxu
在MATLAB环境下设计PCM码的编译码，并对比不同情况下的的编码进行对比。(In MATLAB environment design PCM code encoding and decoding, compare and contrast the different circumstances of the coding)
- 2013-05-05 14:02:25下载
- 积分：1
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最小二乘拟合，kf
包括两个简单卡尔曼滤波例子和一个最小二乘法例程(Filtering and least squares)
- 2017-10-07 15:04:35下载
- 积分：1
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work
matlab 关于association rule 的自己写的函数，有3个文件,
association.m：h = association(m, i, j)
i=>j, m是数据，h是support和confidence，该函数只适用于单个数据
ass_item: h=ass_itset(m, a, b)
同上，但是可用于多个数据（m为数组）
assrule: h = assrule(m, threshold1, threshold2)
该函数用于classification， 得到规则，threshold1为要求的support,threshold2为要求的confidence，h 则为符合要求的规则及其support和confidence，前2列为规则，后2列为其support和confidence
(matlab on the association rule to write functions, there are 3 files, association.m: h = association (m, i, j) i => j, m is the data, h is the support and confidence, this function applies only to a single Data
ass_item: h = ass_itset (m, a, b) it is the same as above, but it can be used for multiple data (m can be matrix)
assrule: h = assrule (m, threshold1, threshold2) the function used for classification,get the rules, threshold1 is the require of support, threshold2 is the required of confidence, h is the rules and their support and confidence, the former two columns as a rule, the latter two columns as one of its support and confidence)
- 2009-12-15 02:51:44下载
- 积分：1
