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AFPOWER
State variable representation of the swing equation of
the one-machine system after fault clearance.
- 2014-10-07 14:58:21下载
- 积分：1
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Communication-System-Simulation-5-6
讲述通信系统仿真的基本知识，包括基带数字传输和带限信道的数字传输的内容(Basic knowledge about the communications system simulation, including baseband digital transmission and digital transmission band-limited channel)
- 2013-04-12 13:45:32下载
- 积分：1
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dbsingle1
solar cell for improvment of efficiency
- 2010-07-15 21:45:44下载
- 积分：1
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m06_QASK
设置参数，创建输入信号,计算和显示比特误差率,绘制图形.(Set parameters, create the input signal, calculate and display bit error rate, draw graphics.)
- 2010-11-06 21:17:21下载
- 积分：1
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EXERCICIO5A
single phase active harmonic filter
- 2013-09-08 02:01:24下载
- 积分：1
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dspbuilder
几个用dspbuilder做的例子，其中有dds系统(Dspbuilder to do with a few examples, in which the system has dds)
- 2007-10-20 12:01:16下载
- 积分：1
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DDA_Line
dda画线算法（数值微分法），matlab实现(Line dda algorithm (Numerical Differentiation), matlab achieve)
- 2009-04-19 22:09:36下载
- 积分：1
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Matlabchengux
说明： matla的100个实用程序，是你学习常用函数必备的资料(matla 100 utility, is that you learn the information necessary common functions)
- 2010-04-28 09:11:20下载
- 积分：1
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shenjingwangluo
T=[1 0 0 1 0 0 1 0 0
0 1 0 0 1 0 0 1 0
0 0 1 0 0 1 0 0 1]
输入向量的最大值和最小值
threshold=[0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1]
net=newff(threshold,[31 3],{ tansig , logsig }, trainlm )
训练次数为1000，训练目标为0.01，学习速率为0.1
net.trainParam.epochs=1000
net.trainParam.goal=0.01
LP.lr=0.1
net = train(net,P,T)
测试数据，和训练数据不一致
P_test=[0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319
0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 (T = [1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1 0 0 0 1 0 0 1 0 0 1] ' of the maximum and minimum input vector threshold = [0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1 0 1] net = newff (threshold, [31 3], {' tansig' , ' logsig' }, ' trainlm' ) training times for the 1000 target of 0.01 training, learning rate of 0.1 net.trainParam.epochs = 1000 net. trainParam.goal = 0.01 LP.lr = 0.1 net = train (net, P, T) test data, and training data inconsistencies P_test = [0.2101 0.0950 0.1298 0.1359 0.2601 0.1001 0.0753 0.0890 0.0389 0.1451 0.0128 0.1590 0.2452 0.0512 0.1319 0.2593 0.1800 0.0711 0.2801 0.1501 0.1298 0.1001 0.1891 0.2531 0.0875 0.0058 0.1803 0.0992 0.0802 0.1002 )
- 2011-05-21 16:47:44下载
- 积分：1
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Untitled3
当小球自由落体时，弹地后运动轨迹的仿真程序！(When the ball free fall, the situation of the trajectory will be simulated!)
- 2014-08-31 10:04:30下载
- 积分：1
