Skip Navigation

IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences 2008 E91-A(4):943-950; doi:10.1093/ietfec/e91-a.4.943
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Alert me to new issues of the journal
Right arrow Add to My Personal Archive
Right arrow Download to citation manager
Right arrow Request Permissions
Google Scholar
Right arrow Articles by SVEHOLM, J.
Right arrow Articles by NAKAJIMA, K.
Social Bookmarking
Add to CiteULike   Add to Connotea   Add to Del.icio.us  
What's this?

Copyright © 2008 The Institute of Electronics, Information and Communication Engineers

Special Section on Selected Papers from the 20th Workshop on Circuits and Systems in Karuizawa -- Papers

Recalling Temporal Sequences of Patterns Using Neurons with Hysteretic Property

Johan SVEHOLM1, Yoshihiro HAYAKAWA1 and Koji NAKAJIMA1

1 The authors are with Laboratory for Brainware Systems, Laboratory for Nanoelectronics and Spintronics, Research Institute of Electrical Communication, Tohoku University, Sendai-shi, 980-8577 Japan. E-mail: johan{at}nakajima.riec.tohoku.ac.jp


  Abstract

Further development of a network based on the Inverse Function Delayed (ID) model which can recall temporal sequences of patterns, is proposed. Additional advantage is taken of the negative resistance region of the ID model and its hysteretic properties by widening the negative resistance region and letting the output of the ID neuron be almost instant. Calling this neuron limit ID neuron, a model with limit ID neurons connected pairwise with conventional neurons enlarges the storage capacity and increases it even further by using a weightmatrix that is calculated to guarantee the storage after transforming the sequence of patterns into a linear separation problem. The network's tolerance, or the model's ability to recall a sequence, starting in a pattern with initial distortion is also investigated and by choosing a suitable value for the output delay of the conventional neuron, the distortion is gradually reduced and finally vanishes.

Key Words: temporal sequences of patterns, limit inverse function delayed neuron, negative resistance

Manuscript received July 2, 2007. Manuscript revised October 6, 2007.


Add to CiteULike CiteULike   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us    What's this?




Disclaimer:
Please note that abstracts for content published before 1996 were created through digital scanning and may therefore not exactly replicate the text of the original print issues. All efforts have been made to ensure accuracy, but the Publisher will not be held responsible for any remaining inaccuracies. If you require any further clarification, please contact our Customer Services Department.