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M-System 的查询结果
matlab例程 产生两个均值为m,方差为sgma的高斯随机变量
产生两个均值为m,方差为sgma的高斯随机变量,当输入参数只有一个时,认为均值为0。
matlab例程 生成M序列的经典代码
生成M序列的经典代码,可以生成不同基数的M序列
matlab例程 1、工具箱:LS_SVMlab Classification_LS_SVMlab.m - 多类分类 Regression_LS_SVMlab.m - 函数拟合 2、工具箱:OSU_SVM3.
1、工具箱:LS_SVMlab
Classification_LS_SVMlab.m - 多类分类
Regression_LS_SVMlab.m - 函数拟合
2、工具箱:OSU_SVM3.00
Classification_OSU_SVM.m - 多类分类
3、工具箱:stprtool\svm
Classification_stprtool.m - 多类分类
4、工具箱:SVM_SteveGunn
Classification_SVM_SteveGunn.m - 二类分类
Regression_SVM_St ...
matlab例程 GA/SVM 程序包含三个文件: 1。MainGA12.m 2。selectGA12.m 3。svmc12.m MainGA12.m是主文件
GA/SVM 程序包含三个文件:
1。MainGA12.m
2。selectGA12.m
3。svmc12.m
MainGA12.m是主文件,其余两个是被调用文件。
MainGA12.m里主要设置有关参数。
=====================
MainGA12.m文件有关设置的说明:
12行:
host= \gatest\ %在matlab的安装盘,例如c:\下设置的程序运行结果目录。 ...
嵌入式Linux TI DaVinci EVM 基于达芬奇技术的TMS320DM6446 Digital Media System-on-Chip的Bootloader源代码!
TI DaVinci EVM 基于达芬奇技术的TMS320DM6446 Digital Media System-on-Chip的Bootloader源代码!
文章/文档 The cable compensation system is an experiment system that performs simulations of partial or microg
The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller(FCMAC) is proposed to contr ...
matlab例程 基于PN序列的同步仿真链路(simulink+m files)
基于PN序列的同步仿真链路(simulink+m files),收端算法为接受序列与本地序列求滑动相关。
matlab例程 MIMO多径瑞利信道下的迫零+串行干扰抵消+自适应功率分配预编码算法仿真链路(simulink+m files)
MIMO多径瑞利信道下的迫零+串行干扰抵消+自适应功率分配预编码算法仿真链路(simulink+m files)
系统设计方案 具体功能: The documentation of Windows system service dependence, it also introduce a service software a
具体功能: The documentation of Windows system service dependence, it also introduce a service software and brief implementation of service dependency
matlab例程 % binomial.m by David Terr, Raytheon, 5-11-04, from mathworks.com % Given nonnegative integers n an
% binomial.m by David Terr, Raytheon, 5-11-04, from mathworks.com
% Given nonnegative integers n and m with m<=n, compute the
% binomial coefficient n choose m.