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LTE_Downlink[1]
维也纳大学，LTE-A下行链路matlab链路级仿真程序。(University of Vienna, LTE-A downlink link level simulation matlab program.)
- 2021-02-02 19:39:59下载
- 积分：1
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Matlab5
：介绍遣传算法的基本原理和Matlab的遗传算法优化工具箱(GAOT)，分析了优化工具函数。探讨Matlab遗传算法工具箱在
参数优化和非线性规划中的应用。通过优化实例，说明遗传算法是一种具有良好的全局寻优性能的优化方法。用Maflab语
言及Maflab语言编制的优化工具箱进行优化设计具有语言简单、函数丰富、用法比较灵活、编程效率高等特点。(: Removal algorithm introduce the basic principles and Matlab Genetic Algorithm Optimization Toolbox (GAOT), an analysis of function optimization tool. Explore the Matlab Genetic Algorithm Toolbox in the parameter optimization and nonlinear programming applications. Through optimization examples to illustrate the genetic algorithm is a good global optimization method to optimize performance. Maflab language and using language Maflab Optimization Toolbox to optimize the design of the language is simple, function-rich, and using more flexible programming and high efficiency.)
- 2007-09-07 20:15:26下载
- 积分：1
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KPP
使用块匹配法的三步搜索对视频中的两帧图象进行预测编码(Use block matching method for video of the three-step searching two frames image forecast coding)
- 2010-07-02 21:56:56下载
- 积分：1
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qiaoliangjiance
这是可以用于数据频谱分析的源程序代码，使用MATLAB编写而成的(This is can be used in the source code of the data spectrum analysis, the use of MATLAB written in)
- 2012-06-04 15:03:01下载
- 积分：1
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blochs
This is a simple, yet useful Bloch equation simulator that runs in Matlab. It is written as a MEX function so that it can run reasonably quickly, and simulate RF and a 1D gradient waveform. Simulations can be run for a range of spatial offsets and frequency offsets.
- 2014-10-14 13:33:05下载
- 积分：1
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SPEA2
SPEA1 Algorithm for matlab
Just run and enjoy
- 2013-04-20 20:50:53下载
- 积分：1
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GA4matlab
遗传算法的matlab实现！~~~~~~~~~(Matlab genetic algorithm to achieve! ~~~~~~~~~)
- 2010-03-08 17:55:15下载
- 积分：1
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wavedec
说明： 小波分解程序 把一副图像用小波进行分解 已达到增强图像的目的(Decomposition process to an image using wavelet decomposition has reached the purpose of enhancing the image)
- 2011-04-06 18:44:09下载
- 积分：1
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loan_and_payment
MATLAB scripts for loan and payment calculations.
- 2010-05-07 06:53:59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
