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pcgames_DotA_im_3.80
sift匹配程序在matlab环境下的实现，包括特征提取与匹配(the sift match program realization in Matlab environment, including feature extraction and matching)
- 2012-04-02 13:19:06下载
- 积分：1
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gbvs
gbvs 提取显著区域，进行其他的程序编写。在matlab上运行，先安装，后可以直接运行(gbvs select main object)
- 2013-04-04 16:28:48下载
- 积分：1
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evaluation
估计理论，关于目标估计的基本知识,常用的最小二乘估计，方差估计等(evaluation theroy)
- 2014-06-15 00:13:07下载
- 积分：1
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informationTheoryToolboxv1.0
信息理论用的工具包，算法已经很全了matlab编写的(Information theory with the toolkit, the algorithm is already very wide, prepared by the matlab)
- 2007-12-18 14:03:41下载
- 积分：1
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pos
关于matlab编程的粒子群算法的重要参考(Matlab programming on an important reference for PSO)
- 2011-04-26 11:10:45下载
- 积分：1
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12
说明： 最大信噪比盲源分离算法
该算法参考文为 给予最大信噪比的盲源分离算法 《计算机仿真》 2006.2(Maximum signal to noise ratio Blind source separation)
- 2011-05-09 16:46:16下载
- 积分：1
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Radar-signal-processing
雷达信号的基本模型，高斯分布，几何分布，求信号的概率分布，概率密度函数，功率谱函数，自相关函数等等(The basic model of the radar signal, Gaussian distribution, geometric distribution, the probability distribution for the signal, probability density function, power spectrum, the autocorrelation function, and so)
- 2013-08-27 11:10:48下载
- 积分：1
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MUSIC_algorithm
MUSIC 算法是利用接收数据的协方差矩阵(Rx)分离出信号子空间和噪声子空间，利用信号方向向量与噪声子空间的正交性来构成空间扫描谱，进行全域搜索谱峰，从而实现信号的参数估计。(MUSIC algorithm is used to receive data covariance matrix (Rx) to isolate the signal subspace and noise subspace, using the signal direction vector and noise subspace orthogonality to form the spatial scan spectrum, full-domain search peaks in order to achieve signal The parameter estimation.)
- 2010-01-13 16:25:43下载
- 积分：1
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yiqunsuanfa
说明： 采用最新的人工智能算法，对城市问题（tsp）问题进行了很好的解决(Using the latest artificial intelligence algorithms, to urban problems (tsp) had a very good problem to solve)
- 2009-08-11 14:18:49下载
- 积分：1
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ELM
训练集/测试集产生
load spectra_data.mat
随机产生训练集和测试集
temp = randperm(size(NIR,1))
训练集——50个样本
P_train = NIR(temp(1:50),:)
T_train = octane(temp(1:50),:)
测试集——10个样本
P_test = NIR(temp(51:end),:)
T_test = octane(temp(51:end),:)
N = size(P_test,2)
数据归一化
( Training set/test set generation load spectra_data.mat randomly generated training set and test set temp = randperm (size (NIR, 1)) training set- 50 samples P_train = NIR (temp (1:50) ,:)' T_train = octane (temp (1:50 ),:)' test set- 10 samples P_test = NIR (temp (51: end ),:)' T_test = octane (temp (51 : end ),:)' N = size (P_test, 2) Data Normalization)
- 2011-05-21 16:45:51下载
- 积分：1
