A Spiking Neural Network for Gas Discrimination Using a Tin Oxide Sensor Array

D
DELTA
2008
4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008)
Abstract - A Spiking Neural Network for Gas Discrimination Using a Tin Oxide Sensor Array

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4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008)

January 23-January 25

ISBN: 978-0-7695-3110-6

	ASCII Text	x
	Maxime Ambard, Bin Guo, Dominique Martinez, Amine Bermak, "A Spiking Neural Network for Gas Discrimination Using a Tin Oxide Sensor Array," Electronic Design, Test and Applications, IEEE International Workshop on, pp. 394-397, 4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008), 2008.

	BibTex	x
	@article{ 10.1109/DELTA.2008.116, author = {Maxime Ambard and Bin Guo and Dominique Martinez and Amine Bermak}, title = {A Spiking Neural Network for Gas Discrimination Using a Tin Oxide Sensor Array}, journal ={Electronic Design, Test and Applications, IEEE International Workshop on}, volume = {0}, year = {2008}, isbn = {978-0-7695-3110-6}, pages = {394-397}, doi = {http://doi.ieeecomputersociety.org/10.1109/DELTA.2008.116}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Electronic Design, Test and Applications, IEEE International Workshop on TI - A Spiking Neural Network for Gas Discrimination Using a Tin Oxide Sensor Array SN - 978-0-7695-3110-6 SP394 EP397 A1 - Maxime Ambard, A1 - Bin Guo, A1 - Dominique Martinez, A1 - Amine Bermak, PY - 2008 KW - Tin Oxide KW - Gas Sensor Array KW - Spike TimingComputation KW - Supervised Learning VL - 0 JA - Electronic Design, Test and Applications, IEEE International Workshop on ER -

Maxime Ambard

Bin Guo

Dominique Martinez

Amine Bermak

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/DELTA.2008.116

We propose a bio-inspired signal processing method for odor discrimination. A spiking neural network is trained with a supervised learning rule so as to classify the analog outputs from a monolithic 4x4 tin oxide gas sensor array implemented in our in-house 5 micrometers process. This scheme has been sucessfully tested on a discrimination task between 4 gases (hydrogen, ethanol, carbon monoxide, methane). Performance compares favorably to the one obtained with a common statistical classifier. Moreover, the simplicity of our method makes it well suited for building dedicated hardware for processing data from gas sensor arrays.

Index Terms:

Tin Oxide, Gas Sensor Array, Spike TimingComputation, Supervised Learning

Citation:

Maxime Ambard, Bin Guo, Dominique Martinez, Amine Bermak, "A Spiking Neural Network for Gas Discrimination Using a Tin Oxide Sensor Array," delta, pp.394-397, 4th IEEE International Symposium on Electronic Design, Test and Applications (delta 2008), 2008

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