Artificial Spiking Neurons and Analog-to-Digital-to-Analog Conversion
Summary :
This paper studies encoding/decoding function of artificial spiking neurons. First, we investigate basic characteristics of spike-trains of the neurons and fix parameter value that can minimize variation of spike-train length for initial value. Second we consider analog-to-digital encoding based upon spike-interval modulation that is suitable for simple and stable signal detection. Third we present a digital-to-analog decoder in which digital input is applied to switch the base signal of the spiking neuron. The system dynamics can be simplified into simple switched dynamical systems and precise analysis is possible. A simple circuit model is also presented.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E91-A No.6 pp.1455-1462
- Publication Date
- 2008/06/01
- Publicized
- Online ISSN
- 1745-1337
- DOI
- 10.1093/ietfec/e91-a.6.1455
- Type of Manuscript
- PAPER
- Category
- Nonlinear Problems
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
Hiroyuki TORIKAI, Aya TANAKA, Toshimichi SAITO, "Artificial Spiking Neurons and Analog-to-Digital-to-Analog Conversion" in IEICE TRANSACTIONS on Fundamentals,
vol. E91-A, no. 6, pp. 1455-1462, June 2008, doi: 10.1093/ietfec/e91-a.6.1455.
Abstract: This paper studies encoding/decoding function of artificial spiking neurons. First, we investigate basic characteristics of spike-trains of the neurons and fix parameter value that can minimize variation of spike-train length for initial value. Second we consider analog-to-digital encoding based upon spike-interval modulation that is suitable for simple and stable signal detection. Third we present a digital-to-analog decoder in which digital input is applied to switch the base signal of the spiking neuron. The system dynamics can be simplified into simple switched dynamical systems and precise analysis is possible. A simple circuit model is also presented.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1093/ietfec/e91-a.6.1455/_p
Copy
@ARTICLE{e91-a_6_1455,
author={Hiroyuki TORIKAI, Aya TANAKA, Toshimichi SAITO, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={Artificial Spiking Neurons and Analog-to-Digital-to-Analog Conversion},
year={2008},
volume={E91-A},
number={6},
pages={1455-1462},
abstract={This paper studies encoding/decoding function of artificial spiking neurons. First, we investigate basic characteristics of spike-trains of the neurons and fix parameter value that can minimize variation of spike-train length for initial value. Second we consider analog-to-digital encoding based upon spike-interval modulation that is suitable for simple and stable signal detection. Third we present a digital-to-analog decoder in which digital input is applied to switch the base signal of the spiking neuron. The system dynamics can be simplified into simple switched dynamical systems and precise analysis is possible. A simple circuit model is also presented.},
keywords={},
doi={10.1093/ietfec/e91-a.6.1455},
ISSN={1745-1337},
month={June},}
Copy
TY - JOUR
TI - Artificial Spiking Neurons and Analog-to-Digital-to-Analog Conversion
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1455
EP - 1462
AU - Hiroyuki TORIKAI
AU - Aya TANAKA
AU - Toshimichi SAITO
PY - 2008
DO - 10.1093/ietfec/e91-a.6.1455
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E91-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 2008
AB - This paper studies encoding/decoding function of artificial spiking neurons. First, we investigate basic characteristics of spike-trains of the neurons and fix parameter value that can minimize variation of spike-train length for initial value. Second we consider analog-to-digital encoding based upon spike-interval modulation that is suitable for simple and stable signal detection. Third we present a digital-to-analog decoder in which digital input is applied to switch the base signal of the spiking neuron. The system dynamics can be simplified into simple switched dynamical systems and precise analysis is possible. A simple circuit model is also presented.
ER -
English
