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fastica
fast ICA的源文件 独立成分分析 MATLAB工具箱里也有 可以下载到工具箱 安装后就可以使用了(fast ICA Independent component analysis of the source file MATLAB toolbox is also available for download to install, ready to use the toolbox)
- 2010-09-14 15:15:10下载
- 积分：1
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Horn-Schunck
光流场 的经典算法，matlab程序，可直接用(Optical Flow Field：Horn-Schunck)
- 2011-04-27 09:45:47下载
- 积分：1
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Chapter_1_NEW_ALG
convex optimizationconvex optimization algo new mit dimtri bertskas lesson 1
- 2015-02-08 07:41:14下载
- 积分：1
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featureselection
sbs和sfs特征提取的MatLAB源代码用于多维向量提取最优(sbs Feature Extraction)
- 2009-03-23 15:46:26下载
- 积分：1
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FLOWMATLAB
电力系统潮流计算 运用MATLAB软件来实现这一功能(Power Flow using MATLAB software to achieve this functionality)
- 2010-05-15 18:00:00下载
- 积分：1
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chap5_02_PP_STC
系统辨识和自适应控制中极点配置间接自矫正控制(Poles indirectly control the correction
in System identification and adaptive control
)
- 2012-07-01 15:16:03下载
- 积分：1
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yunchouxue
运筹学资料加程序,运输问题的合理方案下载。(yunchouxue )
- 2013-07-13 21:16:52下载
- 积分：1
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mnf变换代码
基于MATLAB编程的最小噪声分离方法处理高光谱影像（Minimum Noise Separation Method Based on MATLAB Programming for Hyperspectral Image Processing）(Minimum Noise Separation Method Based on MATLAB Programming for Hyperspectral Image Processing)
- 2019-04-08 20:07:17下载
- 积分：1
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B3g_phase2
B3g_phase2_C语言_Matlab程序及说明(_Matlab Procedures and B3g_phase2_C language description)
- 2007-09-07 10:22:52下载
- 积分：1
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Process
Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage. This paper introduces a new minimum mean square error-based approach to infer the signal subspace in hyperspectral imagery. The method, which is termed hyperspectral signal identification by minimum error, is eigen decomposition based, unsupervised, and fully automatic (i.e., it does not depend on any tuning parameters). It first estimates the signal and noise correlation matrices and then selects the subset of eigenvalues that best represents the signal subspace in the least squared error sense. State-of-the-art performance of the proposed method is illustrated by using simulated and real hyperspectral images.
- 2013-01-01 20:25:49下载
- 积分：1
