Spiking neural network for control chart pattern recognition

D. T. Pham; M. S. Packianather; E. Y A Charles

doi:10.23919/ECC.2007.7068986

Spiking neural network for control chart pattern recognition

D. T. Pham, M. S. Packianather, E. Y A Charles

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

Temporal coding spiking neural networks are receiving wider attention due to their computational power. The coincidence detection property of a spiking neuron, which has no counterpart in a sigmoidal neuron, is one of the reasons for that power. This feature can be utilised to store input information in a network's connection delays and to detect input patterns accurately and efficiently.

Original language	English
Title of host publication	2007 European Control Conference, ECC 2007
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	1392-1397
Number of pages	6
ISBN (Electronic)	9783952417386
DOIs	https://doi.org/10.23919/ECC.2007.7068986
Publication status	Published - 26 Mar 2015
Event	2007 9th European Control Conference, ECC 2007 - Kos, Greece Duration: 2 Jul 2007 → 5 Jul 2007

Conference

Conference	2007 9th European Control Conference, ECC 2007
Country/Territory	Greece
City	Kos
Period	2/07/07 → 5/07/07

ASJC Scopus subject areas

Control and Systems Engineering

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10.23919/ECC.2007.7068986Licence: None: All rights reserved

Cite this

@inproceedings{9d856ae612f74ec8ae70bf4e75326633,

title = "Spiking neural network for control chart pattern recognition",

abstract = "Temporal coding spiking neural networks are receiving wider attention due to their computational power. The coincidence detection property of a spiking neuron, which has no counterpart in a sigmoidal neuron, is one of the reasons for that power. This feature can be utilised to store input information in a network's connection delays and to detect input patterns accurately and efficiently.",

author = "Pham, {D. T.} and Packianather, {M. S.} and Charles, {E. Y A}",

year = "2015",

month = mar,

day = "26",

doi = "10.23919/ECC.2007.7068986",

language = "English",

pages = "1392--1397",

booktitle = "2007 European Control Conference, ECC 2007",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

note = "2007 9th European Control Conference, ECC 2007 ; Conference date: 02-07-2007 Through 05-07-2007",

}

TY - GEN

T1 - Spiking neural network for control chart pattern recognition

AU - Pham, D. T.

AU - Packianather, M. S.

AU - Charles, E. Y A

PY - 2015/3/26

Y1 - 2015/3/26

N2 - Temporal coding spiking neural networks are receiving wider attention due to their computational power. The coincidence detection property of a spiking neuron, which has no counterpart in a sigmoidal neuron, is one of the reasons for that power. This feature can be utilised to store input information in a network's connection delays and to detect input patterns accurately and efficiently.

AB - Temporal coding spiking neural networks are receiving wider attention due to their computational power. The coincidence detection property of a spiking neuron, which has no counterpart in a sigmoidal neuron, is one of the reasons for that power. This feature can be utilised to store input information in a network's connection delays and to detect input patterns accurately and efficiently.

UR - http://www.scopus.com/inward/record.url?scp=84927728894&partnerID=8YFLogxK

U2 - 10.23919/ECC.2007.7068986

DO - 10.23919/ECC.2007.7068986

M3 - Conference contribution

AN - SCOPUS:84927728894

SP - 1392

EP - 1397

BT - 2007 European Control Conference, ECC 2007

PB - Institute of Electrical and Electronics Engineers (IEEE)

T2 - 2007 9th European Control Conference, ECC 2007

Y2 - 2 July 2007 through 5 July 2007

ER -

Spiking neural network for control chart pattern recognition

Abstract

Conference

ASJC Scopus subject areas

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