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code for face align using ica (independent component analysis) .a good code for reaserch .
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盲源分离算法的几篇文章应用
【基于独立分量分析的脑电中眼电伪迹消除】【基于负熵和智能优化的盲源分离方法】【基于小波消噪和盲源分离的信号奇异点检测方法】-Blind source separation algorithm applied 【several articles based on independent component analysis of EEG ocular artifact】 【intelligent optimization based on negative entr
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In frequency-domain blind source separation (BSS) for speech with independent component analysis (ICA), a practical parametric Pearson distribution system is used to model the distribution of frequency-domain source signals.-In frequency-domain blin
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机器学习和模式识别的常用算法，独立主元分析，常用于人脸图像识别。此压缩包含有完整的用于人脸图像的算法源码-Commonly used machine learning and pattern recognition algorithms, independent component analysis, commonly used for facial image recognition, speech recognition, etc.
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ICA独立成分分析是近年研究的主流，此资料室介绍ICA的基础资料-ICA Independent component analysis of the mainstream in recent years, the basis of this information Reference Room descr iption ICA
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独立分量分析的程序，MATLAB环境下编写的，采用的是JADE方法，可用来进行盲源分离-Independent component analysis program, MATLAB environment prepared by the JADE method can be used for blind source separation
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非线性独立分量分析(ICA)源码,主要是用于非线性ICA进行盲源分离算法的函数-Nonlinear independent component analysis (ICA) source, mainly for non-linear ICA for blind source separation algorithm function
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很好很强大的独立分量分析程序，这个大家都可以用来-A very powerful independent component analysis program, take a look at this we all can be used to
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关于独立成份分析中的若干算法的程序,一个优化的计算四阶ICA/BSS的算法-a number of source code about independent component analysis algorithm.A computationally optimized fourth-order based ICA/BSS algorithm
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FAST ICA，fast independent component analysis，用于分解独立的component-FAST ICA, fast independent component analysis, independent component used to decompose
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ICA算法可以将噪声信号分解为一系列独立的分量（ICs），这样就可以对各独立分量进行单独的研究和分析。首先叙述了柴油机噪声信号的特性。预测模型表明：发动机噪声信号满足ICA计算的要求。然后介绍了ICA模型的相关理论。举例说明ICA方法分离信号的有效性，以及ICA方法对小能量噪声的分离的有效性。连续小波变换来显示了各独立分量ICs在时频域内的特性。由采集信号分离得到噪声源信号可以作为发动机的理论预测和设计依据。-he ICA algorithm can be decomposed into a s
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This matlab code demonstrates independent component analysis.
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提出了一种改进的独立分量分析方法对脑电信号进行去伪迹消噪，取得了相当不错的效果-An improved method of independent component analysis to EEG artifact noise cancellation, very good results achieved
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由Hao Shen, Stefanie Jegelka, and Arthur Gretton提供的Fast Kernel ica算法。-Fast Kernel Independent Component Analysis using an Approximate Newton Method by Hao Shen, Stefanie Jegelka, and Arthur Gretton
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还参考量独立分量分析(ICA-R)程序与文档-Also refers to the amount of independent component analysis (ICA-R) procedure and documentation
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快速独立成分分析的matlab示例程序，包括全部工具箱程序。很好用。-Fast Independent Component Analysis of the matlab example programs, including all the toolbox program. Good use.
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基于fast独立分量分析方法实现盲源分离-Fast independent component analysis method based on blind source separation to achieve
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Independent Component Analysis of Edge Information
for Face Recognition
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这是一个关于盲源分离独立成分分析方法，效果很好-Here is a blind source separation independent component analysis
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这是基于负熵方法的音频信号分离的固定点独立分量分析方法的Matlab程序。-This is based on negative entropy method of audio signal separation of fixed-point independent component analysis of the Matlab program.
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