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A Neural Networks Based on Structural Characteristics of Cerebral Neocortex

[+] Author Affiliations
Ryo Hasegawa, Toshihiko Shiraishi, Shin Morishita

Yokohama National University, Yokohama, Japan

Paper No. IMECE2008-67213, pp. 79-86; 8 pages
doi:10.1115/IMECE2008-67213
From:
  • ASME 2008 International Mechanical Engineering Congress and Exposition
  • Volume 14: New Developments in Simulation Methods and Software for Engineering Applications
  • Boston, Massachusetts, USA, October 31–November 6, 2008
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-4875-3 | eISBN: 978-0-7918-3840-2
  • Copyright © 2008 by ASME

abstract

Artificial neural networks have been applied to pattern recognition, prediction and control because they have abilities of learning, generalization and nonlinear mapping. These conventional neural networks have not had “intelligence” yet. In pattern recognition, the recognition rate can be low when there are some noises in recognized patterns. Not so many neural networks have been reported that introduce the structural and functional characteristics of the brain obtained by the progress of neurophysiology. In this study, we focused on the cerebral neocortex, which is the most developed in human to be compared with the other animals and deals with recognition, language and imagination, introduced its characteristics of uniform, hierarchical, column structures and six layers to neural networks and investigated the possibility of emerging its functional characteristics of the human brain.

Copyright © 2008 by ASME

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