Spiking Neural Network Inter-Spike Time Based Decoding Scheme
Summary :
Information transmission among biological neurons is carried out by a complex series of spike signals. The input inter-spike arrival times at a neuron are believed to carry information which the neurons utilize to carry out a task. In this paper, a new scheme which utilizes the input inter-spike intervals (ISI) for decoding an input spike train is proposed. A spike train consists of a sequence on input spikes with various inter-spike times. This decoding scheme can also be used for neurons which have multiple synaptic inputs but for which each synapse receives a single spike within one input time window. The ISI decoding neural network requires only a few neurons. Example applications show the usefulness of the decoding scheme.
- Publication
- IEICE TRANSACTIONS on Information Vol.E88-D No.8 pp.1893-1902
- Publication Date
- 2005/08/01
- Publicized
- Online ISSN
- DOI
- 10.1093/ietisy/e88-d.8.1893
- Type of Manuscript
- Special Section PAPER (Special Section on Recent Advances in Circuits and Systems--Part 2)
- Category
- Neural Networks and Fuzzy Systems
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
Hesham H. AMIN, Robert H. FUJII, "Spiking Neural Network Inter-Spike Time Based Decoding Scheme" in IEICE TRANSACTIONS on Information,
vol. E88-D, no. 8, pp. 1893-1902, August 2005, doi: 10.1093/ietisy/e88-d.8.1893.
Abstract: Information transmission among biological neurons is carried out by a complex series of spike signals. The input inter-spike arrival times at a neuron are believed to carry information which the neurons utilize to carry out a task. In this paper, a new scheme which utilizes the input inter-spike intervals (ISI) for decoding an input spike train is proposed. A spike train consists of a sequence on input spikes with various inter-spike times. This decoding scheme can also be used for neurons which have multiple synaptic inputs but for which each synapse receives a single spike within one input time window. The ISI decoding neural network requires only a few neurons. Example applications show the usefulness of the decoding scheme.
URL: https://global.ieice.org/en_transactions/information/10.1093/ietisy/e88-d.8.1893/_p
Copy
@ARTICLE{e88-d_8_1893,
author={Hesham H. AMIN, Robert H. FUJII, },
journal={IEICE TRANSACTIONS on Information},
title={Spiking Neural Network Inter-Spike Time Based Decoding Scheme},
year={2005},
volume={E88-D},
number={8},
pages={1893-1902},
abstract={Information transmission among biological neurons is carried out by a complex series of spike signals. The input inter-spike arrival times at a neuron are believed to carry information which the neurons utilize to carry out a task. In this paper, a new scheme which utilizes the input inter-spike intervals (ISI) for decoding an input spike train is proposed. A spike train consists of a sequence on input spikes with various inter-spike times. This decoding scheme can also be used for neurons which have multiple synaptic inputs but for which each synapse receives a single spike within one input time window. The ISI decoding neural network requires only a few neurons. Example applications show the usefulness of the decoding scheme.},
keywords={},
doi={10.1093/ietisy/e88-d.8.1893},
ISSN={},
month={August},}
Copy
TY - JOUR
TI - Spiking Neural Network Inter-Spike Time Based Decoding Scheme
T2 - IEICE TRANSACTIONS on Information
SP - 1893
EP - 1902
AU - Hesham H. AMIN
AU - Robert H. FUJII
PY - 2005
DO - 10.1093/ietisy/e88-d.8.1893
JO - IEICE TRANSACTIONS on Information
SN -
VL - E88-D
IS - 8
JA - IEICE TRANSACTIONS on Information
Y1 - August 2005
AB - Information transmission among biological neurons is carried out by a complex series of spike signals. The input inter-spike arrival times at a neuron are believed to carry information which the neurons utilize to carry out a task. In this paper, a new scheme which utilizes the input inter-spike intervals (ISI) for decoding an input spike train is proposed. A spike train consists of a sequence on input spikes with various inter-spike times. This decoding scheme can also be used for neurons which have multiple synaptic inputs but for which each synapse receives a single spike within one input time window. The ISI decoding neural network requires only a few neurons. Example applications show the usefulness of the decoding scheme.
ER -
English
