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
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;
Journal_Title :
Systems, Man and Cybernetics, IEEE Transactions on
DOI :
10.1109/TSMC.1983.6313068