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shujufenxi
Matlab经典算法之数据分析,概率统计,回归等程序(Matlab classical algorithm of data analysis, probability and statistics, regression and other procedures)
- 2011-07-09 11:08:45下载
- 积分:1
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feature-extraction
主要应用于两幅图片比对时,对两幅图片进行校准(Mainly used in the two pictures, two pictures calibration)
- 2013-01-07 22:22:51下载
- 积分:1
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m_seq
本程序用simulink仿真m序列做扩频码时系统的性能(The procedures used m sequence simulink simulation performance of the system when the spreading codes)
- 2012-04-25 10:55:51下载
- 积分:1
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读取sgy文件并成图
说明: 读取sgy格式数据,并利用wigb进行成图(Read sgy format data, and use wigb to map)
- 2019-04-29 17:44:17下载
- 积分:1
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read_letter
this is create letters using matlab
- 2012-08-03 17:01:18下载
- 积分:1
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LMS
本算法为自适应LMS算法,本算法研究了步长对,权初值,以及是否归一化对算法的影响(The algorithm for the adaptive LMS algorithm, the algorithm of the steps right, the right initial value, and whether the normalization of the algorithm)
- 2011-10-04 12:30:57下载
- 积分:1
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clean
研究上课所讲谱分析方法,利用实验验证书中的结论,掌握各种谱分析方法,学会实验设计和实验结果分析。
所应用到的谱分析方法,包括:
1) 非参数化方法:周期图(直接法)、BT法(间接法),Welch平均周期图法
2) 参数化方法: RELAX、Capon
3) 空间谱估计:常见的DOA方法(Capon)
(Experimental Objective: To study methods of spectral analysis class talking about the use of experimental verification of the conclusions of the book, to master a variety of spectral analysis methods, learn experimental design and experimental results. Experiment content: applied to the spectral analysis methods, including: 1) non-parametric methods: periodogram (direct method), BT method (indirect method), Welch average periodogram 2) parameterization: RELAX, Capon 3) spatial spectrum estimation: common of DOA method (Capon))
- 2011-11-28 10:15:15下载
- 积分:1
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Principal-component-analysis
主成份分析法在证券市场个股评价中的应用,可以用SPSS软件解决(Principal component analysis in the stock market evaluation of individual stocks, you can use SPSS software to solve)
- 2011-09-02 19:33:00下载
- 积分:1
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PhC_waveguide_distribution
field distrubution of PhC
- 2011-05-07 20:20:37下载
- 积分:1
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gm11
function exp85
clear all
p=[0:0.1:1.1]
t=[22.4570 26.6012 12.6416 5.9367 6.9265 28.2432 31.5068 37.0166 7.8947 1.0398 12.7095]
net=newff([0 1],[5 1],{ tansig purelin }, traingdx , learngdm )
net.trainParam.epochs=2500
net.trainParam.goal=0.001
net.trainParam.show=50
net=train(net,p,t)
r=sim(net,p)
plot(p,t,p,r, * )
y=sim(net,[1.2])
- 2012-04-26 12:14:11下载
- 积分:1