Location:
Search - icaml
Search list
Description: 用最大相似性方法实现独立分量分析算法的matlab代码，可用于盲信号处理和图像滤波器构造。-with the greatest similarity method independent component analysis algorithm Matlab code can be used to blind signal processing and image filter structure.
Platform: |
Size: 7549 |
Author: 李彪 |
Hits:
Description: ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
-ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
Platform: |
Size: 2772862 |
Author: 海心 |
Hits:
Description: ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the number of classes and produces keywords for each class. The icaML algorithm is used.
-ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the number of classes and produces keywords for each class. The icaML algorithm is used.
Platform: |
Size: 2496134 |
Author: 海心 |
Hits:
Description: fastica用于信号处理的源码程序，希望大家好好研究，应用实际
Platform: |
Size: 7623 |
Author: scz |
Hits:
Description: he 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: 7730 |
Author: 薛耀斌 |
Hits:
Description: This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
Platform: |
Size: 7664 |
Author: 陈互 |
Hits:
Description: This a Bayesian ICA algorithm for the linear instantaneous mixing model with additive Gaussian noise [1]. The inference problem is solved by ML-II, i.e. the sources are found by integration over the source posterior and the noise covariance and mixing matrix are found by maximization of the marginal likelihood [1]. The sufficient statistics are estimated by either variational mean field theory with the linear response correction or by adaptive TAP mean field theory [2,3]. The mean field equations are solved by a belief propagation method [4] or sequential iteration. The computational complexity is N M^3, where N is the number of time samples and M the number of sources.
Platform: |
Size: 7168 |
Author: 陈互 |
Hits:
Description: 用最大相似性方法实现独立分量分析算法的matlab代码，可用于盲信号处理和图像滤波器构造。-with the greatest similarity method independent component analysis algorithm Matlab code can be used to blind signal processing and image filter structure.
Platform: |
Size: 7168 |
Author: 李彪 |
Hits:
Description: ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
-ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
Platform: |
Size: 2772992 |
Author: 海心 |
Hits:
Description: ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the number of classes and produces keywords for each class. The icaML algorithm is used.
-ICA is used to classify text in extension to the latent semantic indexing framework. ICA show to align the context grouping structure well in a human sense [1], thus can be used for unsupervised classification. The demonstration shows this on medical abstracts (MED dataset), that uses BIC to estimate the number of classes and produces keywords for each class. The icaML algorithm is used.
Platform: |
Size: 2495488 |
Author: 海心 |
Hits:
Description: fastica用于信号处理的源码程序，希望大家好好研究，应用实际-FastICA source for the signal processing procedures, hope that we make good research, practical
Platform: |
Size: 7168 |
Author: scz |
Hits:
Description: he 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: 7168 |
Author: 薛耀斌 |
Hits:
Description: 独立分量分析的matla b源代码。可用于盲信号处理和信号分离等等。-Independent Component Analysis matla b source code. Can be used in signal processing and blind signal separation and so on.
Platform: |
Size: 7168 |
Author: xu |
Hits: