Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits - Couverture souple

Florescu, Dorian

9783319860725: Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits

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ISBN 10 : 3319860720 ISBN 13 : 9783319860725

Editeur : Springer, 2018

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This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.

A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.

Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.

A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of alinear filter, given the input of the filter encoded with the same neuron model.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

� propos de l?auteur

Dr Dorian Florescu is currently a Postdoctoral Research Fellow in the Department of Automatic Control and Systems Engineering at the University of Sheffield, working on the 'Digital Fruit Fly Brain' project, funded jointly by BBSRC and the National Science Foundation.

He was awarded the BEng degree in Systems Engineering from the Technical University of Iasi, Romania, in 2011 and the PhD degree in Automatic Control & Systems Engineering from the University of Sheffield

Les informations fournies dans la section � A propos du livre � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: Springer
Date d'�dition: 2018
Langue: anglais
ISBN 10: 3319860720
ISBN 13: 9783319860725
Reliure: Broch�
Nombre de pages: 156
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Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits

Dorian Florescu

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Nominated&nbspas an&nbspoutstanding Ph.D. thesis by the University of SheffieldReformulates, for the first time, the encoding performed by the integrate-and-fire neuron model as a problem of uniform sampling of an auxiliary function on a set of . N� de r�f. du vendeur 448759646

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Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits

Dorian Florescu

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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of alinear filter, given the input of the filter encoded with the same neuron model. N� de r�f. du vendeur 9783319860725

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Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits

Dorian Florescu

Edit� par Springer International Publishing Jul 2018, 2018

ISBN 10 : 3319860720 ISBN 13 : 9783319860725

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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of a linear filter, given the input of the filter encoded with the same neuron model. 156 pp. Englisch. N� de r�f. du vendeur 9783319860725

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Florescu, Dorian

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Reconstruction, Identification and Implementation Methods for Spiking Neural Circuits

Dorian Florescu

Edit� par Springer International Publishing, Springer International Publishing Jul 2018, 2018

ISBN 10 : 3319860720 ISBN 13 : 9783319860725

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Taschenbuch. Etat : Neu. Neuware -This work is motivated by the ongoing open question of how information in the outside world is represented and processed by the brain. Consequently, several novel methods are developed.A new mathematical formulation is proposed for the encoding and decoding of analog signals using integrate-and-fire neuron models. Based on this formulation, a novel algorithm, significantly faster than the state-of-the-art method, is proposed for reconstructing the input of the neuron.Two new identification methods are proposed for neural circuits comprising a filter in series with a spiking neuron model. These methods reduce the number of assumptions made by the state-of-the-art identification framework, allowing for a wider range of models of sensory processing circuits to be inferred directly from input-output observations.A third contribution is an algorithm that computes the spike time sequence generated by an integrate-and-fire neuron model in response to the output of alinear filter, given the input of the filter encoded with the same neuron model.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 156 pp. Englisch. N� de r�f. du vendeur 9783319860725

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