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dc.contributor.authorTayarani, Mohammad
dc.contributor.authorSchmuker, Michael
dc.date.accessioned2021-06-14T16:15:01Z
dc.date.available2021-06-14T16:15:01Z
dc.date.issued2021-05-31
dc.identifier.citationTayarani , M & Schmuker , M 2021 , ' Address-Event Signal Processing: Silicon Retina, Cochlea and Olfaction A Review ' , Frontiers in Neural Circuits , vol. 15 , 610446 . https://doi.org/10.3389/fncir.2021.610446
dc.identifier.urihttp://hdl.handle.net/2299/24583
dc.description© 2021 Tayarani-Najaran and Schmuker. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). https://creativecommons.org/licenses/by/4.0/
dc.description.abstractThe nervous systems converts the physical quantities sensed by its primary receptors into trains of events that are then processed in the brain. The unmatched efficiency in information processing has long inspired engineers to seek brain-like approaches to sensing and signal processing. The key principle pursued in neuromorphic sensing is to shed the traditional approach of periodic sampling in favor of an the event-driven scheme that mimicks sampling as it occurs in the nervous system, where events are preferably emitted upon the change of the sensed stimulus. In this paper we highlight the advantages and challenges of event-based sensing and signal processing in the visual, auditory and olfactory domains. We also provide a survey of the literature covering neuromorphic sensing and signal processing in all three modalities. Our aim is to facilitate research in event-based sensing and signal processing by providing a comprehensive overview of the research performed previously as well as highlighting conceptual advantages, current progress and future challenges in the field.en
dc.format.extent31
dc.format.extent1000877
dc.language.isoeng
dc.relation.ispartofFrontiers in Neural Circuits
dc.titleAddress-Event Signal Processing: Silicon Retina, Cochlea and Olfaction A Reviewen
dc.contributor.institutionCentre for Computer Science and Informatics Research
dc.contributor.institutionSchool of Physics, Engineering & Computer Science
dc.contributor.institutionDepartment of Computer Science
dc.contributor.institutionCentre of Data Innovation Research
dc.contributor.institutionBiocomputation Research Group
dc.description.statusPeer reviewed
rioxxterms.versionofrecord10.3389/fncir.2021.610446
rioxxterms.typeOther
herts.preservation.rarelyaccessedtrue


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