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MIMLdros
包括MATLAB的代码:MIMLSVM+和E-MIMLSVM+(MIMLdros includes the MATLAB codes of MIMLSVM+ and E-MIMLSVM+ which are MIML algorithms that have been applied to drosophila gene expression pattern annotation. The package contains a Readme file which explains how to use it.)
- 2011-05-12 16:26:52下载
- 积分:1
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R-K
用龙格库塔法求解微分方程组初值问题的matlab实例程序(a matlab example program about using Runge-Kutta method to solve the initial value problem of differential equations)
- 2020-07-04 19:00:01下载
- 积分:1
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基于Matlab的双足机器人动力学仿真及仿生控制平台
基于Matlab的双足机器人动力学仿真及仿生控制平台(Dynamic simulation and bionic control platform for Biped Robot Based on Matlab)
- 2018-11-05 11:20:47下载
- 积分:1
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FT-099LD(E)
激光650nm接收器资料,接收光为38Khz可调试光(650nm laser data receivers, the received optical light can be debugged to 38Khz)
- 2011-01-24 16:50:54下载
- 积分:1
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matlabknowlege
包含matlab图像处理的相关算法实现程序(Contains matlab image processing procedures related algorithm)
- 2010-05-10 14:51:34下载
- 积分:1
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WXY_abc_dq100512770SVG
基于simulink的APF系统仿真,主要是采用瞬时无功理论的ip-iq谐波电流提取法。(the simulink model for APF of Three-phase Three-Line Structure)
- 2014-03-27 13:57:26下载
- 积分:1
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crossvalidate
10折交叉验证代码 自编函数 可用于任何数据 直接使用即可(10 fold cross validation code editing the function can be used in any data can be used directly
)
- 2021-02-28 10:29:36下载
- 积分:1
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testFilter
系统传输函数测试,使用扫频法测试已知系统的频响特性并绘制相关的频响图(System transfer function test, frequency sweep method is used to test the frequency response characteristics of the known system, and to draw the relevant frequency response diagram)
- 2017-09-07 16:57:09下载
- 积分:1
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hushifenbianjiaodu
矢量水听器波束形成程序 分辨角度 (Vector Hydrophone beamforming procedures to distinguish the perspective of)
- 2020-11-06 14:59:49下载
- 积分:1
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MATLAB
MATLAB函数参考手册,查看matlab函数作用以及功能。( SVMLSPex02.m
Two Dimension SVM Problem, Two Class and Separable Situation
Difference with SVMLSPex01.m:
Take the Largrange Function (16)as object function insteads ||W||,
so it need more time than SVMLSex01.m
Method from Christopher J. C. Burges:
"A Tutorial on Support Vector Machines for Pattern Recognition", page 9
Objective: min "f(A)=-sum(ai)+sum[sum(ai*yi*xi*aj*yj*xj)]/2" ,function (16)
Subject to: sum{ai*yi}=0 ,function (15)
and ai>=0 for any i, the particular set of constraints C2 (page 9, line14).
The optimizing variables is "Lagrange Multipliers": A=[a1,a2,...,am],m is the number of total samples.)
- 2011-04-27 14:27:35下载
- 积分:1