Art

J-GLOBAL ID：201602259825123915   Reference number：16A1327668

A neural network with a biologically possible architecture can implement Bayesian estimation and reproduce Pieron’s law

ベイズ推定を実現しPieron則を再現することができる生物学的に可能なアーキテクチャをもつニューラルネットワーク

Author (2)： Futagi Daiki (Graduate School of Information Science and Engineering, Ritsumeikan University) ,  Kitano Katsunori (Department of Human and Computer Intelligence, Ritsumeikan University)
Material： Nonlinear Theory and Its Applications, IEICE (Web)  (Nonlinear Theory Its Appl IEICE (Web))
Volume： 7  Issue： 2  Page： 146-155(J-STAGE)  Publication year： 2016 
JST Material Number： U0219A  ISSN： 2185-4106  Document type： Article
Article type： 原著論文  Country of issue： Japan (JPN)  Language： ENGLISH (EN)

Thesaurus term： *Bayes estimation ,  *neural network(biomodel) ,  computer architecture ,  cerebral cortex ,  selection ,  algorithm ,  perception ,  *visual recognition
Semi thesaurus term： architecture ,  *neural network model ,  *visual recognition ,  Discrete choice ,  direction perception

Author keywords (5)： Bayesian estimation theory ,  neural network ,  discrete choice method ,  normalization ,  Pieron’s law

JST classification (2)： Neurocomputers  (JC06010Q) ,  Artificial intelligence  (JE08000Z)

Reference (18)：

• [1] D. Kersten, P. Mamassian, and A. Yuille, “Object perception as Bayesian inference,” Annu. Rev. Psychol., vol. 55, pp. 271-304, 2004.
• [2] K.P. Koding and D.M. Wolpert, “Bayesian integration in sensorimotor learning,” Nature, vol. 427, no. 6971, pp. 244-247, 2004.
• [3] K. Doya, S. Ishii, A. Pouget, and R.P.N. Rao, Bayesian Brain: Probabilistic Approaches to Neural Coding, MIT Press, Cambridge, Massachusetts, 2007.
• [4] R.P.N. Rao, “Bayesian computation in recurrent neural circuits,” Neural Comput., vol. 16, no. 1, pp. 1-38, 2004.
• [5] K.E. Train, Discrete choice methods with simulation, Cambridge University Press, Cambridge, U.K., 2003.

Terms in the title (4)： ベイズ推定 ,  生物学 ,  アーキテクチャ ,  ニューラルネットワーク