Literature DB >> 1606245

"Live" neuron and optimal learning rule.

L B Emelyanov-Yaroslavsky1, V I Potapov.   

Abstract

A concept of the live unit as an automatic regulation system with a few admissible states areas in the space of states is considered. Energetic profit of oscillatory behavior consisting in the consecutive transitions of system from one admissible states area to another is shown. It is stated, that external disturbances cause the energy consumption of oscillatory system to decrease. On the basis of this concept and some neurophysiological data, the "live" energy-consuming nonlinear three-state neuron model is proposed and the existence of energy optimal generation frequency v(opt) is proved. For the realization of tendency to v(opt) the optimal learning rule is proposed, which provides unsupervised learning and interlinked short-term and long-term memories with forgetting. The model proposed explains the genesis of neural network, is promising in the sense of network self-organization and allows to solve the problem of internal activity in the researches on artificial intelligence.

Mesh:

Year:  1992        PMID: 1606245     DOI: 10.1007/bf00201803

Source DB:  PubMed          Journal:  Biol Cybern        ISSN: 0340-1200            Impact factor:   2.086


  2 in total

1.  Neural networks and physical systems with emergent collective computational abilities.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1982-04       Impact factor: 11.205

2.  Neurons with graded response have collective computational properties like those of two-state neurons.

Authors:  J J Hopfield
Journal:  Proc Natl Acad Sci U S A       Date:  1984-05       Impact factor: 11.205

  2 in total
  2 in total

1.  Self-organization of day cycle and hierarchical associative memory in "live" neural network.

Authors:  L B Emelyanov-Yaroslavsky; V I Potapov
Journal:  Biol Cybern       Date:  1992       Impact factor: 2.086

2.  Emergence of Leadership in Communication.

Authors:  Armen E Allahverdyan; Aram Galstyan
Journal:  PLoS One       Date:  2016-08-17       Impact factor: 3.240

  2 in total

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