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dc.creatorJiménez Fernández, Ángel Franciscoes
dc.creatorCerezuela Escudero, Elenaes
dc.creatorMiró Amarante, María Lourdeses
dc.creatorDomínguez Morales, Manuel Jesúses
dc.creatorGómez Rodríguez, Francisco de Asíses
dc.creatorLinares Barranco, Alejandroes
dc.creatorJiménez Moreno, Gabrieles
dc.date.accessioned2019-07-08T09:03:55Z
dc.date.available2019-07-08T09:03:55Z
dc.date.issued2017
dc.identifier.citationJiménez Fernández, Á.F., Cerezuela Escudero, E., Miró Amarante, M.L., Domínguez Morales, M.J., Gómez Rodríguez, F.d.A., Linares Barranco, A. y Jiménez Moreno, G. (2017). A Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approach. IEEE Transactions on Neural Networks and Learning Systems, 28 (4), 804-818.
dc.identifier.issn2162-237Xes
dc.identifier.urihttps://hdl.handle.net/11441/87909
dc.description.abstractThis paper presents a new architecture, design flow, and field-programmable gate array (FPGA) implementation analysis of a neuromorphic binaural auditory sensor, designed completely in the spike domain. Unlike digital cochleae that decompose audio signals using classical digital signal processing techniques, the model presented in this paper processes information directly encoded as spikes using pulse frequency modulation and provides a set of frequency-decomposed audio information using an address-event representation interface. In this case, a systematic approach to design led to a generic process for building, tuning, and implementing audio frequency decomposers with different features, facilitating synthesis with custom features. This allows researchers to implement their own parameterized neuromorphic auditory systems in a low-cost FPGA in order to study the audio processing and learning activity that takes place in the brain. In this paper, we present a 64-channel binaural neuromorphic auditory system implemented in a Virtex-5 FPGA using a commercial development board. The system was excited with a diverse set of audio signals in order to analyze its response and characterize its features. The neuromorphic auditory system response times and frequencies are reported. The experimental results of the proposed system implementation with 64-channel stereo are: a frequency range between 9.6 Hz and 14.6 kHz (adjustable), a maximum output event rate of 2.19 Mevents/s, a power consumption of 29.7 mW, the slices requirements of 11 141, and a system clock frequency of 27 MHz.es
dc.description.sponsorshipMinisterio de Economía y Competitividad TEC2012-37868-C04-02es
dc.description.sponsorshipJunta de Andalucía P12-TIC-1300es
dc.formatapplication/pdfes
dc.language.isoenges
dc.publisherIEEE Computer Societyes
dc.relation.ispartofIEEE Transactions on Neural Networks and Learning Systems, 28 (4), 804-818.
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAddress eventes
dc.subjectArtificial cochleaes
dc.subjectFPGAes
dc.subjectNeuromorphic engineeringes
dc.subjectPulse frequency modulation (PFM)es
dc.subjectReal-time auditiones
dc.titleA Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approaches
dc.typeinfo:eu-repo/semantics/articlees
dcterms.identifierhttps://ror.org/03yxnpp24
dc.type.versioninfo:eu-repo/semantics/submittedVersiones
dc.rights.accessrightsinfo:eu-repo/semantics/openAccesses
dc.contributor.affiliationUniversidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadoreses
dc.relation.projectIDTEC2012-37868-C04-02es
dc.relation.projectIDP12-TIC-1300es
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/7523402es
dc.identifier.doi10.1109/TNNLS.2016.2583223es
dc.contributor.groupUniversidad de Sevilla. TEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitación
idus.format.extent14es
dc.journaltitleIEEE Transactions on Neural Networks and Learning Systemses
dc.publication.volumen28es
dc.publication.issue4es
dc.publication.initialPage804es
dc.publication.endPage818es
dc.identifier.sisius21292096es

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