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AGuideToMATLABOOProgramming
说明： 电子书：使用Maltab进行面向对象的编程(A Guide To MATLAB OO Programming)
- 2009-08-07 22:25:16下载
- 积分：1
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pso
一种比较高效的微粒群算法源码。效率比基本pso高很多(an efficient pso code)
- 2011-07-21 09:18:59下载
- 积分：1
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Del1
it is .rar file.it contains some source codes..
- 2011-08-23 13:27:27下载
- 积分：1
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Improving-Dictionary-Learning
PDF+论文算法实现源代码"Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reuse"由莱斯利N.史密斯和迈克尔·埃拉德，IEEE信号处理快报（2013年）(PDF+ thesis algorithm source code " Improving Dictionary Learning: Multiple Dictionary Updates and Coefficient Reuse" by the Er Ai Leslie N. Smith and Mike Ladd, IEEE Signal Processing Letters (2013))
- 2014-01-12 23:27:57下载
- 积分：1
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practisef
matlab基础学习资料，包括例题，答案，讲解，符号运算，图像，矩正等(matlab-based learning information, including sample questions, answers, explanations, operator symbols, images, moments, etc. are)
- 2008-04-03 14:31:51下载
- 积分：1
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SVM_iris
matlab，K折交叉验证，SVM方法对IRIS分类(K-flod,matlab ,svm method)
- 2021-04-10 18:38:59下载
- 积分：1
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fan_motor
this is the fan speed motor control that input is torque and output is speed
- 2014-02-25 21:07:43下载
- 积分：1
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ode_trap
说明： matlab中关于数值分析的一个matlab源程序(numerical analysis matlab on a matlab source)
- 2011-03-11 09:45:54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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plot_Jakes_model
描绘出衰落信道中Jakes模型 此为主函数体 并在主函数中调用jakes模型(Jakes model depicts Fading This is the main body of the function in the main function call jakes model)
- 2013-07-23 10:10:58下载
- 积分：1
