Description: In ICA, multi-dimensional data is decomposed into components that are maximally independent in an appropriate sense (kurtosis and negentropy, in this package).the ICA components have maximal statistical independence. In practice, ICA can often uncover disjoint underlying trends in multi-dimensional data.
To Search:
File list (Check if you may need any files):
| Filename | Size | Date |
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| arrinit.m | 747 | 2001-06-04
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| back.m | 900 | 2001-06-04
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| compdist.m | 658 | 2000-07-06
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| compgrad.m | 1136 | 2001-06-04
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| costderiv.m | 2860 | 2001-06-04
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| doepoch.m | 384 | 2001-06-04
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| forward.m | 747 | 2001-06-04
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| forwardg.m | 914 | 2001-06-04
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| generate.m | 1708 | 2001-06-04
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| netinit.m | 1702 | 2000-08-03
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| netpar.m | 533 | 2001-06-04
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| plotdata.m | 2340 | 2001-06-04
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| processdata.m | 820 | 2001-06-04
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| reportresults.m | 137 | 2001-06-04
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| testcost.m | 2614 | 2001-06-04
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| train.m | 329 | 2005-02-01
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| wadapt.m | 2029 | 2001-06-04
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| MIToolbox Manual.pdf | 50771 | 2005-02-03
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| readme.html | 6385 | 2005-02-03 |
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