IEICE TRANSACTIONS on Fundamentals
Recalling Temporal Sequences of Patterns Using Neurons with Hysteretic Property
Summary :
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.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.4 pp.943-950
- Publication Date
- 2008/04/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.4.943
- Type of Manuscript
- Special Section PAPER (Special Section on Selected Papers from the 20th Workshop on Circuits and Systems in Karuizawa)
- Category
Authors
Keyword
Latest Issue
Copyrights notice of machine-translated contents
The copyright of the original papers published on this site belongs to IEICE. Unauthorized use of the original or translated papers is prohibited. See IEICE Provisions on Copyright for details.
Cite this
Copy
Johan SVEHOLM, Yoshihiro HAYAKAWA, Koji NAKAJIMA, "Recalling Temporal Sequences of Patterns Using Neurons with Hysteretic Property" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 4, pp. 943-950, April 2008, doi: 10.1093/ietfec/e91-a.4.943.
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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.4.943/_p
Copy
@ARTICLE{e91-a_4_943,
author={Johan SVEHOLM, Yoshihiro HAYAKAWA, Koji NAKAJIMA, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Recalling Temporal Sequences of Patterns Using Neurons with Hysteretic Property},
year={2008},
volume={E91-A},
number={4},
pages={943-950},
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.},
keywords={},
doi={10.1093/ietfec/e91-a.4.943},
ISSN={1745-1337},
month={April},}
Copy
TY - JOUR
TI - Recalling Temporal Sequences of Patterns Using Neurons with Hysteretic Property
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 943
EP - 950
AU - Johan SVEHOLM
AU - Yoshihiro HAYAKAWA
AU - Koji NAKAJIMA
PY - 2008
DO - 10.1093/ietfec/e91-a.4.943
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 4
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - April 2008
AB - 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.
ER -
English
