DocumentCode
2004604
Title
Silicon neuron design based on phase reduction analysis
Author
Nakada, Kaoru ; Miura, Kiyotaka ; Asai, Tetsuya
Author_Institution
Adv. Electron. Res. Div., Kyushu Univ., Fukuoka, Japan
fYear
2012
fDate
20-24 Nov. 2012
Firstpage
1059
Lastpage
1062
Abstract
In this paper, we propose a dynamical system design approach for silicon neurons (SiNs) based on the phase reduction theory. The design approaches for SiNs can be classified as three: the phenomenological design, the conductance-based design, and the dynamical systems design. As a part of the third approach, we propose the phase response curve (PRC)-based design for SiNs to enhance synchronization in an ensembles of SiNs. We consider the key criteria to optimize SiN design in terms of phase response properties by analyzing various circuit models of previous SiNs. Furthermore, as a case study, we demonstrate how to tune circuit parameters to obtain a desirable PRC of a resonate-and-fire neuron (RFN) circuit. Finally, we discuss the possibility of extending our approach to design a class of the generalized integrate-and-fire neuron (GIFN) circuits including the Izhikevich type SiNs.
Keywords
learning (artificial intelligence); neural chips; synchronisation; Izhikevich type silicon neuron; PRC-based design; RFN circuit; conductance-based design; dynamical system design approach; ensemble synchronization; generalization; phase reduction analysis; phase response curve; phase response property; phenomenological design; resonate-and-fire neuron circuit; silicon neuron design;
fLanguage
English
Publisher
ieee
Conference_Titel
Soft Computing and Intelligent Systems (SCIS) and 13th International Symposium on Advanced Intelligent Systems (ISIS), 2012 Joint 6th International Conference on
Conference_Location
Kobe
Print_ISBN
978-1-4673-2742-8
Type
conf
DOI
10.1109/SCIS-ISIS.2012.6505177
Filename
6505177
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