DocumentCode
1298816
Title
Field theory of self-organizing neural nets
Author
Amari, Shun-ichi
Author_Institution
Dept. of Math. Engng. & Instrumentation Phys., Univ. of Tokyo, Tokyo, Japan
Issue
5
fYear
1983
Firstpage
741
Lastpage
748
Abstract
A field theory is proposed as a mathematical method for analyzing learning and self-organizing nerve nets and systems in a unified manner. It is shown by the use of the theory that a nerve net has an ability for automatically forming categorizers or signal detecting cells for the signals which the net receives from its environment. Moreover, when the set of signals has a topological structure, the detectors are arranged in the nerve system (or field) to preserve the topology, so that the topographical structure is introduced in the nerve system by self-organization.
Keywords
brain models; learning systems; neural nets; self-adjusting systems; topology; field theory; self-organizing neural nets; signal detecting cells; Equations; Feature extraction; Mathematical model; Neurons; Organizations; Retina; Vectors;
fLanguage
English
Journal_Title
Systems, Man and Cybernetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9472
Type
jour
DOI
10.1109/TSMC.1983.6313068
Filename
6313068
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