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pole
小车-倒立摆的平衡控制问题,由强化学习方法来求解,参考sutton《强化学习》一书(cart-pole balancing control problem,reinforcement learning algortihm is used here, please refer to Sutton s book ,named 《reinforcement learning》)
- 2012-03-06 15:09:20下载
- 积分:1
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woking-with-large-images
ufldl,working with large images 作业,完整代码,运行结果与提示一致(ufldl, working with large images operations, the complete code, operating results consistent with the prompt)
- 2014-12-11 20:04:19下载
- 积分:1
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xbwmcwtd
采用加权网络中节点强度和权重都是幂率分布的模型,加入重复控制,通过matlab代码,可以动态调节运行环境的参数,包括脚本文件和函数文件形式。( Using weighted model nodes in the network strength and weight are power law distribution, Join repetitive control, By matlab code, Can dynamically adjust the parameters of the operating environment, Including script files and function files in the form.)
- 2016-03-22 23:41:00下载
- 积分:1
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Band
计算光子晶体能带结构图的MATLAB源码文件,使用的方法为平面波展开。各物理参数均有注释,光子晶体结构可任意调整。(Calculation of photonic band structure of the MATLAB source code files, the methods used for the plane wave expansion. The physical parameters have comments, photonic crystal structure can be adjusted.)
- 2021-03-16 17:49:21下载
- 积分:1
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matlabhanshu2003
说明: matlab函数大全,2003,挺有用的(matlab function Daquan, 2003)
- 2010-04-23 08:40:47下载
- 积分:1
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mimojihe
mimo2乘2矩阵的仿真与应用,内有源码与注释源码,方便阅读理解(mimo2 by 2 matrix of simulation and application source code and comments within the source code to facilitate reading comprehension)
- 2010-05-11 21:35:25下载
- 积分:1
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ARFIMA222
说明: 基于长记性特征的时间序列预测模型,很好用,准确度优于普通神经网络,我自己一直在用(Characteristics based on long memory time series forecasting model, the good, the accuracy is better than an ordinary neural network, I have been using)
- 2011-03-09 10:49:03下载
- 积分:1
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stimulation_equlizer
书后习题:信道均衡的简单仿真。适合入门的同学使用。(Book exercises: a simple simulation of channel equalization. Students for entry-use.)
- 2013-04-12 21:25:27下载
- 积分:1
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LMS_mb_nc
noise canceller using lms
- 2012-02-13 06:31:50下载
- 积分:1
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LSSVM
最小二乘支持向量机,程序粘到command window里,设定 2 两个参数,可以更改,以达到最优化(igam=0.001
isig2=0.001
[gam,sig2]=tunelssvm({X,Y, f ,igam,isig2, RBF_kernel },...
[0.001 0.001 10000 10000], gridsearch ,{}, leaveoneout_lssvm )
type= function approximation
kernel= RBF_kernel
model=initlssvm(X,Y,type,gam,sig2,kernel)
model
model=trainlssvm(model)
Yt=simlssvm(model,Xt) )
- 2015-12-27 11:05:14下载
- 积分:1