Talk:Independent component analysis

The definition of negentropy you have linked to does not seem relevant to this article; could you update the negentropy article to explain the term as used in ICA literature? Thanks --Chinasaur 00:37, 16 Jun 2005 (UTC)

In literature, approximations to negentropy are not really used to separate signals. Most ICA methods are derived from the maximum likelihood theory, which is equivalent to the infoMAX theory. Both maximize the network entropy, so most methods are approximations to network entropy instead of approximations to negentropy.

See Survey on Independent Component Analysis by Aapo Hyvärinen

For a definition of negentropy see mentioned survey or the paper by

P. Comon, Independent Component Analysis - a new concept?, Signal Processing, 36:287-314, 1994. JasperKlewer 10:27, 21 March 2006 (UTC)

definition needs cleanup

Was the definition copied from another source and taken out-of-context? As a mathematician, I find it incomprehensible. Lavaka 17:33, 16 August 2006 (UTC)

I am requesting that this article be made less esoteric. Many terms must be taken for granted if the definition is thought to be meaningful. Wilgamesh 21:06, 20 August 2007 (UTC)

Copyviol

• Source: http://www.cnl.salk.edu/~tewon/ICA/preface.html (1998)
• Diff: [1] (2005)
• No authorization is included.
• Text removed

--F. Cosoleto 16:14, 17 January 2007 (UTC)

Number of sources

The intro said: the ICA methods are not able to extract the actual number of source signals, the order of the source signals, nor the signs or the scales of the sources. But Sepp Hochreiter and Jürgen Schmidhuber showed how to obtain non-linear ICA or source separation as a by-product of regularization (1999). Their method does not require a priori knowledge about the number of independent sources.

So I changed this to: most ICA methods. Algorithms 16:18, 7 June 2007 (UTC)