Physics – Condensed Matter – Disordered Systems and Neural Networks
Scientific paper
1997-06-11
Physics
Condensed Matter
Disordered Systems and Neural Networks
LaTeX archive, no figures, 10 pages, to appear in Phil. Mag
Scientific paper
The ideas of optimization of learning algorithms in Artificial Neural Networks are reviewed emphasizing generic properties and the online implementations are interpreted from a biological perspective. A simple model of the relevant subsidiary variables needed to improve learning in artificial feedforward networks and the `time ordering' of the appearance of the respective information processing systems is proposed. We discuss the possibility that these results might be relevant in other contexts, not being restricted to the simple models from which they stem. The analysis of a few examples, which range from the lowest cellular scale to the macroscopic level, suggests that similar ideas could be applied to biological systems.
Caticha Nestor
Kinouchi Osame
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