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henhaodeshenjingwangluo
这是中国数学建模中编程交流上神经网络内容,里面提供了很多神经网络的例子(This is the mathematical modeling of neural networks on the content of the exchange program, which provides many examples of neural network)
- 2010-11-20 19:45:52下载
- 积分:1
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shortestpath
基于WLAN室内无线环境,针对点到点之间的最短路径的采用floyd等算法实现仿真。(WLAN-based indoor wireless environment, the shortest path between point for the adoption of such floyd algorithm simulation.)
- 2013-09-11 16:42:28下载
- 积分:1
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paso-banda
esta es una simulacion de un filtro pasa banda y paso alto muy conveniente para el uso en ingenieria electronica
- 2011-12-07 23:39:09下载
- 积分:1
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c6s2
单机无穷大系统仿真。电压恒定,励磁稀疏改变(Machine infinite system simulation. Constant voltage excitation sparse change)
- 2014-03-11 22:30:04下载
- 积分:1
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16.LCMV波束形成算法MATLAB程序
16.LCMV波束形成算法MATLAB程序(matlab code for LCMV beamforming algorithm)
- 2018-04-27 20:55:17下载
- 积分:1
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matlab
matlab 输入输出小例子 输入输出小例子(matlab input/output small example)
- 2013-08-19 17:42:48下载
- 积分:1
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piecewise-linear
Digital image processing, polygonal approximation piecewise-linear method
- 2011-05-21 00:34:12下载
- 积分:1
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gads
遗传算法工具包,matlab 7.0包含了这个工具箱,matlab7.0以前的版本没有这个工具箱,雷英杰编著《Matlab遗传算法工具箱及应用》对这个工具箱的使用进行了介绍(Genetic Algorithm Toolkit, matlab 7.0 contains the toolbox, matlab7.0 previous versions do not have this toolbox, LEI Ying-jie edited )
- 2007-10-18 10:55:32下载
- 积分:1
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rocket
实现火箭的垂直发射,并在重力作用下实现转弯。(Achieve vertical launch rocket and turn under the influence of gravity.)
- 2013-09-30 10:43:25下载
- 积分:1
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music(doa)
七单元天线阵MUSIC DOA估计:
d=1 , 天线阵元的间距;
lma=2, 信号中心波长;
四输入信号;
A=[A1,A2,A3,A4], 得出A矩;
四信号的频率d=[1.3*cos(v1*n)
1*sin(v2*n)
1*sin(v3*n)
1*sin(v4*n)]
构造输入信号矢量
U=A*d
总的输入信号
总输入信号的协方差矩阵
[s,h]=eig(c)
求协方差的特征矢量及特征值
取出与零特征值对应的特征矢量
求协方差矩阵的逆矩阵
应用Music法估计输出
绘出各波达方向图(Seven-element antenna array MUSIC DOA estimates: d = 1, Antenna Array pitch LMA = 2 signal center wavelength four input signals A = [A1, A2, A3, and A4], drawn A moment tetra-frequency of the signal D = [1.3* cos (V1* n) 1* sin (v2* n) 1* sin (v3* n) 1* sin (V4* n)] constructed input signal vector U = A* D of the total input signal of the total input signal covariance matrix [S] = EIG (c) seeking covariance feature vector and the feature value removing and corresponding to the zero eigenvalues characterized vector seeking covariance matrix inverse matrix Applications Music estimate output plotted DOA Figure)
- 2013-04-15 23:48:49下载
- 积分:1