Table of Contents
Advances in Artificial Neural Systems
Volume 2009, Article ID 846040, 11 pages
http://dx.doi.org/10.1155/2009/846040
Research Article

Building Recurrent Neural Networks to Implement Multiple Attractor Dynamics Using the Gradient Descent Method

Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako City, Saitama 351-0198, Japan

Received 31 March 2008; Accepted 22 August 2008

Academic Editor: Akira Imada

Copyright © 2009 Jun Namikawa and Jun Tani. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Jun Namikawa and Jun Tani, “Building Recurrent Neural Networks to Implement Multiple Attractor Dynamics Using the Gradient Descent Method,” Advances in Artificial Neural Systems, vol. 2009, Article ID 846040, 11 pages, 2009. https://doi.org/10.1155/2009/846040.