Memory trace in spiking neural networks
Autor(en): | Castellano, M. Pipa, G. |
Stichwörter: | Continuous delayed systems; delayed-dynamical systems; Dynamical systems; History dependencies; Information exchanges; Intelligent agents, Neural networks; Limited memory; memory trace; Neural computations; reservoir computing; spiking neural networks; Spiking neuron, Computer architecture | Erscheinungsdatum: | 2013 | Journal: | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | Volumen: | 8131 LNCS | Startseite: | 264 | Seitenende: | 271 | Zusammenfassung: | Spiking neural networks have a limited memory capacity, such that a stimulus arriving at time t would vanish over a timescale of 200-300 milliseconds [1]. Therefore, only neural computations that require history dependencies within this short range can be accomplished. In this paper, the limited memory capacity of a spiking neural network is extended by coupling it to an delayed-dynamical system. This presents the possibility of information exchange between spiking neurons and continuous delayed systems. © 2013 Springer-Verlag Berlin Heidelberg. |
Beschreibung: | Conference of 23rd International Conference on Artificial Neural Networks, ICANN 2013 ; Conference Date: 10 September 2013 Through 13 September 2013; Conference Code:99717 |
ISBN: | 9783642407277 | ISSN: | 03029743 | DOI: | 10.1007/978-3-642-40728-4_33 | Externe URL: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84884922381&doi=10.1007%2f978-3-642-40728-4_33&partnerID=40&md5=6aeeb94a998000c70fd7bddddd2ae370 |
Zur Langanzeige
Seitenaufrufe
7
Letzte Woche
0
0
Letzter Monat
0
0
geprüft am 04.05.2024