Persistent Memory in Single Node Delay-Coupled Reservoir Computing

Bitte benutzen Sie diese Kennung, um auf die Ressource zu verweisen:
https://osnadocs.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2017032715753
Open Access logo originally created by the Public Library of Science (PLoS)
Langanzeige der Metadaten
DC ElementWertSprache
dc.creatorKovac, André David
dc.creatorKoall, Maximilian
dc.creatorPipa, Gordon
dc.creatorToutounji, Hazem
dc.date.accessioned2017-03-27T07:32:19Z
dc.date.available2017-03-27T07:32:19Z
dc.date.issued2017-03-27T07:32:19Z
dc.identifier.citationPLoS ONE, Vol. 11, No. 10: e0165170, S. 1-15
dc.identifier.urihttps://osnadocs.ub.uni-osnabrueck.de/handle/urn:nbn:de:gbv:700-2017032715753-
dc.description.abstractDelays are ubiquitous in biological systems, ranging from genetic regulatory networks and synaptic conductances, to predator/pray population interactions. The evidence is mounting, not only to the presence of delays as physical constraints in signal propagation speed, but also to their functional role in providing dynamical diversity to the systems that comprise them. The latter observation in biological systems inspired the recent development of a computational architecture that harnesses this dynamical diversity, by delay-coupling a single nonlinear element to itself. This architecture is a particular realization of Reservoir Computing, where stimuli are injected into the system in time rather than in space as is the case with classical recurrent neural network realizations. This architecture also exhibits an internal memory which fades in time, an important prerequisite to the functioning of any reservoir computing device. However, fading memory is also a limitation to any computation that requires persistent storage. In order to overcome this limitation, the current work introduces an extended version to the single node Delay-Coupled Reservoir, that is based on trained linear feedback. We show by numerical simulations that adding task-specific linear feedback to the single node Delay-Coupled Reservoir extends the class of solvable tasks to those that require nonfading memory. We demonstrate, through several case studies, the ability of the extended system to carry out complex nonlinear computations that depend on past information, whereas the computational power of the system with fading memory alone quickly deteriorates. Our findings provide the theoretical basis for future physical realizations of a biologically-inspired ultrafast computing device with extended functionality.eng
dc.relationhttp://journals.plos.org/plosone/article?id=10.1371/journal.pone.0165170
dc.rightsNamensnennung 4.0 International-
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/-
dc.subjectMemoryeng
dc.subjectTeacherseng
dc.subjectLong-term memoryeng
dc.subjectSignal filteringeng
dc.subjectDynamical systemseng
dc.subjectNeural networkseng
dc.subjectNonlinear dynamicseng
dc.subjectSignal processingeng
dc.subjectNeuronseng
dc.subject.ddc610 - Medizin und Gesundheit
dc.titlePersistent Memory in Single Node Delay-Coupled Reservoir Computingeng
dc.typeEinzelbeitrag in einer wissenschaftlichen Zeitschrift [article]
dc.identifier.doi10.1371/journal.pone.0165170
vCard.ORGFB8
Enthalten in den Sammlungen:FB08 - Hochschulschriften
Open-Access-Publikationsfonds

Dateien zu dieser Ressource:
Datei Beschreibung GrößeFormat 
Zeitschriftenartikel_PLOS_ONE_11_10_2016_Kovac.PDF3,55 MBAdobe PDF
Zeitschriftenartikel_PLOS_ONE_11_10_2016_Kovac.PDF
Miniaturbild
Öffnen/Anzeigen


Diese Ressource wurde unter folgender Copyright-Bestimmung veröffentlicht: Lizenz von Creative Commons Creative Commons