Reentrant Self-Organizing Map: Toward Brain-Inspired Multimodal Association

Creators: Khacef, Lyes; Rodriguez, Laurent; Miramond, Benoit

Others:: University of Groningen [Groningen]; Laboratoire d'Electronique, Antennes et Télécommunications (LEAT) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA); ANR-17-CE24-0036,SOMA,Auto-organisation dans les architectures matérielles neuromorphiques(2017); ANR-19-P3IA-0002,3IA@cote d'azur,3IA Côte d'Azur(2019)

Description

Local plasticity mechanisms enable our brains to self-organize, both in structure and function, in order to adapt to the environment. This unique property is the inspiration for this study: we propose a brain-inspired computational model for self-organization, then discuss its impact on theclassification accuracy and the energy-efficiency of an unsupervised multimodal association task.

Abstract

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Reentrant Self-Organizing Map: Toward Brain-Inspired Multimodal Association

Description

Abstract

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