Exploration of the dynamics of spiking neural networks / F. Rhéaume, DRDC Valcartier ; D. Grenier, Université Laval. : D68-6/005-2013-1E-PDF

"Liquid state machine is a technique that is well-suited for many spatiotemporal pattern recognition tasks found in defence applications. The technique exploits the complex dynamics of spiking neural networks. In general, Liquid state machines use biologically inspired neuron models such as the leaky-integrate-and-fire model. When structured into a network, leaky-integrate-and-fire neurons interact in a complex and a non-linear manner, making it difficult to understand their behavior in response to an input stimulus. In this memorandum, the response of simple neural systems to input stimulus is studied. The goal is to provide a first exploration of the dynamical state of spiking neurons in reaction to their stimulation by continuous inputs. For this purpose, small neural systems made of, respectively, one single neuron, three serial neurons, and a three-by-three network are analyzed"--Abstract, page i.

Lien permanent pour cette publication :
publications.gc.ca/pub?id=9.882747&sl=1

Renseignements sur la publication
Ministère/Organisme Defence R&D Canada.
Defence R&D Canada - Valcartier.
Titre Exploration of the dynamics of spiking neural networks / F. Rhéaume, DRDC Valcartier ; D. Grenier, Université Laval.
Titre de la série Technical memorandum ; DRDC Valcartier TM 2011-005
Type de publication Série - Voir l'enregistrement principal
Langue [Anglais]
Format Électronique
Document électronique
Note(s) "March 2013."
Includes bibliographical references (pages 23-25).
Includes abstracts and summaries in English and French.
Information sur la publication Quebec (Quebec) : Defence Research and Development Canada - Valcartier, 2013.
©2013
Auteur / Contributeur Rhéaume, François, 1962- author.
Description 1 online resource (x, 26 pages, 2 unnumbered pages) : illustrations (chiefly colour).
Numéro de catalogue
  • D68-6/005-2013-1E-PDF
Descripteurs Neural networks (Computer science)
Réseaux neuronaux (Informatique)
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