Designing simple nonlinear filters using hysteresis of single recurrent neurons for acoustic signal recognition in robots

DC FieldValueLanguage
dc.contributor.authorManoonpong, P.
dc.contributor.authorPasemann, F.
dc.contributor.authorKolodziejski, C.
dc.contributor.authorWörgötter, F.
dc.date.accessioned2021-12-23T16:29:01Z-
dc.date.available2021-12-23T16:29:01Z-
dc.date.issued2010
dc.identifier.isbn9783642158186
dc.identifier.issn03029743
dc.identifier.urihttps://osnascholar.ub.uni-osnabrueck.de/handle/unios/16022-
dc.descriptionConference of 20th International Conference on Artificial Neural Networks, ICANN 2010 ; Conference Date: 15 September 2010 Through 18 September 2010; Conference Code:82138
dc.description.abstractIn this article we exploit the discrete-time dynamics of a single neuron with self-connection to systematically design simple signal filters. Due to hysteresis effects and transient dynamics, this single neuron behaves as an adjustable low-pass filter for specific parameter configurations. Extending this neuro-module by two more recurrent neurons leads to versatile high- and band-pass filters. The approach presented here helps to understand how the dynamical properties of recurrent neural networks can be used for filter design. Furthermore, it gives guidance to a new way of implementing sensory preprocessing for acoustic signal recognition in autonomous robots. © 2010 Springer-Verlag Berlin Heidelberg.
dc.description.sponsorshipEuropean Neural Network Society (ENNS); Aristotle University of Thessaloniki; Alexander TEI of Thessaloniki; University of Macedonia; Democritus University of Thrace; International Hellenic University
dc.language.isoen
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.subjectAcoustic signals
dc.subjectAutonomous robot
dc.subjectDiscrete time dynamics
dc.subjectDynamical properties
dc.subjectFilter designs
dc.subjectHysteresis effect
dc.subjectNonlinear filter
dc.subjectSignal filters
dc.subjectSingle neuron
dc.subjectTransient dynamics, Acoustic waves
dc.subjectBandpass filters
dc.subjectHigh pass filters
dc.subjectHysteresis
dc.subjectLow pass filters
dc.subjectRobots
dc.subjectSignal filtering and prediction
dc.subjectSignal processing, Recurrent neural networks
dc.titleDesigning simple nonlinear filters using hysteresis of single recurrent neurons for acoustic signal recognition in robots
dc.typeconference paper
dc.identifier.doi10.1007/978-3-642-15819-3_50
dc.identifier.scopus2-s2.0-78049410282
dc.identifier.urlhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-78049410282&doi=10.1007%2f978-3-642-15819-3_50&partnerID=40&md5=d3a80cdc0a03a9c6d97f8b9d01cafbc5
dc.description.volume6352 LNCS
dc.description.issuePART 1
dc.description.startpage374
dc.description.endpage383
dc.publisher.placeThessaloniki
dcterms.isPartOf.abbreviationLect. Notes Comput. Sci.
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