Description: 一个ICA工具。This binary version of the runica() function of Makeig et al. contained
in the EEG/ICA Toolbox runs 12x faster than the Matlab version. It uses
the logistic infomax ICA algorithm of Bell and Sejnowski, with natural
gradient and extended ICA extensions. It was programmed for unsupervised
usage by Scott Makeig at CNL, Salk Institute, La Jolla CA. Sigurd Enghoff
translated it into C++ code and compiled it for multiple platforms. J-R
Duann has improved the PCA dimension-reduction and has compiled the
linux and free_bsd versions.
Platform: |
Size: 136032 |
Author:aaaaaaa |
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Description: 用于脑电信号特征提取的InfoMax Algorithm Based on ICA；也可以稍作改动用于其他信息提取。-for feature extraction InfoMax Algorithm Based on ICA; Minor modifications can be used to extract other information. Platform: |
Size: 217816 |
Author:wyh |
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Description: ICA算法The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.-ICA algorithm:The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction. Platform: |
Size: 563873 |
Author:陈互 |
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Description: 用于脑电信号特征提取的InfoMax Algorithm Based on ICA；也可以稍作改动用于其他信息提取。-for feature extraction InfoMax Algorithm Based on ICA; Minor modifications can be used to extract other information. Platform: |
Size: 217088 |
Author:wyh |
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Description: ICA算法The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction.-ICA algorithm:The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The number of independent components are calculated using Bayes Information Criterion [3] (BIC), with PCA for dimension reduction. Platform: |
Size: 563200 |
Author:陈互 |
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Description: 一种新的ica算法，主要是应用与盲分离算法，大家可以-ica a new algorithm, and are primarily used to blind separation algorithm, we can s Platform: |
Size: 362496 |
Author:sunz |
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Description: 用于脑电信号特征提取的InfoMax Algorithm Bassed on ICA；也能稍作改动用于其他信息提取。
-Feature extraction for EEG InfoMax Algorithm Bassed on ICA minor modifications for other information extraction. Platform: |
Size: 218112 |
Author:mikeche |
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Search - infomax ICA algorithm