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matlab
适合初学者学习的教程,还有例子.适合电子与通信专业,以及信息工程专业学习熟悉Matlab的教程(Course suitable for beginners to learn, there are examples. Suitable for electronic and communications professionals, and information engineering study are familiar with Matlab tutorial)
- 2008-03-24 20:07:43下载
- 积分：1
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BasedonthePIDControlofDisturbanceObserver
这是一个很好的matlab程序源，能够很好的反映出基于干扰观测器的 PID 控制性能。(This is a good source of matlab programs that can well reflect the disturbance observer-based PID control performance.)
- 2009-11-18 10:02:37下载
- 积分：1
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LMS-by-adian-try
使用LMS算法，对信道模型的估计应用（LMS by adian try）(Using the LMS algorithm for channel estimation applications)
- 2012-04-22 23:28:32下载
- 积分：1
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YUV2RGBfinal.m
图像处理，图像小波变换，svd变换, svd trasnform(Image processing, image wavelet transform, svd transform)
- 2013-04-06 16:22:23下载
- 积分：1
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MATLAB
MATLAB 仿真实现干涉图的程序，仅供参考(MATLAB Simulation interferogram procedures for reference purposes only)
- 2015-02-01 14:07:25下载
- 积分：1
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SVMDTC_close
空间矢量调制用于直接转矩控制，希望可以互相借鉴(Space Vector Modulation in Direct Torque Control )
- 2010-01-05 21:32:18下载
- 积分：1
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QAM_gen1
说明： matlab仿真实现qam信号的产生，用于AWG的波形信号产生等(qam simulation matlab generate signals for the AWG waveform signal generator, etc.)
- 2009-07-22 17:22:59下载
- 积分：1
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rddata
说明： 应用matlab读取MIT-BIH中ECG .dat文件(read the .dat file of ECG signal in MIT database into matlab)
- 2011-02-24 15:44:41下载
- 积分：1
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Vector_Control_SVPWM
vector conducteur pnc fille matlab 2012
- 2012-04-07 17:32:26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
