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pegasos
Pegasos-原始估计分梯度求解支持向量机“
是一种原始的优化支持向量机分类算法解决问题。
请参阅进一步的参考。("Pegasos-Primal Estimated sub-Gradient SOlver for SVM"
is a primal optimization problem solver in Support Vector Machine classification algorithm.
See the paper for further reference.)
- 2011-05-15 17:57:44下载
- 积分:1
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Floyd
对最短路径算法的研究,是matlab的,用于研究最短路径算法(Study on the algorithm of the shortest path, matlab algorithm for the shortest path,)
- 2013-05-08 20:23:05下载
- 积分:1
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GS
说明: 第01章 DB2应用开发概述.rar(Chapter 01 outlines the DB2 application development. Rar)
- 2007-08-04 12:10:59下载
- 积分:1
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R_LDA_PRL
LDA 人脸识别的 程序段 大家下着看看吧 对大家有帮助的(LDA face recognition under the program segment we take a look at the bar for all of us help)
- 2008-12-30 18:22:10下载
- 积分:1
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MATLAB_optical
关于MATLAB编程用两种方法模拟光学实验(MATLAB programming on the optics experiments using two kinds of simulation)
- 2009-12-20 13:48:54下载
- 积分:1
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puxianzengqiang
利用最陡下降法分离宽带和窄带信号,实现谱线增强(you can separate broadband and narrowband signal by the steepest descent method to achieve line enhancement )
- 2010-12-11 09:29:23下载
- 积分:1
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Time-Hopping-UWB
TH-PPM-UWB的simulink仿真框图以及各个部分的S函数(TH-PPM-UWB in the simulink simulation block diagram and various part of the S function)
- 2021-03-22 14:29:16下载
- 积分:1
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sinefitness
Least squares sinusoid fit algorithm described in IEEE Standard for Digitizing Waveform Recorders (IEEE Std 1057): Algorithm for three-parameter and four-parameter least squares fit to sinewave data using matrix operations.
The algorithm is (in most cases) really quick. If the signal frequency is a guess, it has to be close to true frequency value.
For further information, consult IEEE Std 1057 and/or IEEE Std 1241 documentation.
Now also fits complex sinusoids i.e. phasors with noise and o
- 2015-01-24 15:25:16下载
- 积分:1
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choas
混沌序列中不同映射的实现,matlab语言编写(Chaos in different mapping implementations , matlab language
)
- 2012-02-01 15:22:10下载
- 积分:1
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decomp_reconst_WU
Decompose image into subbands (undecimated wavelet), denoise, and recompose again.
fh = decomp_reconst_wavelet(im,Nsc,daub_order,block,noise,parent,covariance,optim,sig)
im : image
Nsc: Number of scales
daub_order: Order of the daubechie fucntion used (must be even).
block: size of neighborhood within each undecimated subband.
noise: image having the same autocorrelation as the noise (e.g., a delta, for white noise)
parent: are we including the coefficient at the central location at the next coarser scale?
covariance: are we considering covariance or just variance?
optim: for choosing between BLS-GSM (optim = 1) and MAP-GSM (optim = 0)
sig: standard deviation (scalar for uniform noise or matrix for spatially varying noise)
Javier Portilla, Univ. de Granada, 3/03
Revised: 11/04
- 2010-08-14 20:29:11下载
- 积分:1