文件名称:icaMF
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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.
相关搜索: ica
infomax
bic
maximum
likelihood
pca
Bayes
Information
Criterion
ICA算法
icaMF
likelihood
主分量分析
infomax
bic
maximum
likelihood
pca
Bayes
Information
Criterion
ICA算法
icaMF
likelihood
主分量分析
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下载文件列表
brain_images.mat
demo_mf.m
digits.mat
icaML.m
ica_adatap.m
ica_adatap_bic.m
speech.mat
demo_mf.m
digits.mat
icaML.m
ica_adatap.m
ica_adatap_bic.m
speech.mat