dc.creator | Cerezuela Escudero, Elena | es |
dc.creator | Jiménez Fernández, Ángel Francisco | es |
dc.creator | Paz Vicente, Rafael | es |
dc.creator | Domínguez Morales, Manuel Jesús | es |
dc.creator | Linares Barranco, Alejandro | es |
dc.creator | Jiménez Moreno, Gabriel | es |
dc.date.accessioned | 2019-12-27T11:56:16Z | |
dc.date.available | 2019-12-27T11:56:16Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Cerezuela Escudero, E., Jiménez Fernández, Á.F., Paz Vicente, R., Domínguez Morales, M.J., Linares Barranco, A. y Jiménez Moreno, G. (2015). Musical notes classification with Neuromorphic Auditory System using FPGA and a Convolutional Spiking Network. En IJCNN 2015 : International Joint Conference on Neural Networks Killarney, Ireland: IEEE Computer Society. | |
dc.identifier.isbn | 978-1-4799-1960-4 | es |
dc.identifier.issn | 2161-4407 | es |
dc.identifier.uri | https://hdl.handle.net/11441/91274 | |
dc.description.abstract | In this paper, we explore the capabilities of a sound
classification system that combines both a novel FPGA cochlear
model implementation and a bio-inspired technique based on a
trained convolutional spiking network. The neuromorphic
auditory system that is used in this work produces a form of
representation that is analogous to the spike outputs of the
biological cochlea. The auditory system has been developed using
a set of spike-based processing building blocks in the frequency
domain. They form a set of band pass filters in the spike-domain
that splits the audio information in 128 frequency channels, 64
for each of two audio sources. Address Event Representation
(AER) is used to communicate the auditory system with the
convolutional spiking network. A layer of convolutional spiking
network is developed and trained on a computer with the ability
to detect two kinds of sound: artificial pure tones in the presence
of white noise and electronic musical notes. After the training
process, the presented system is able to distinguish the different
sounds in real-time, even in the presence of white noise. | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad TEC2012-37868-C04-02 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | IJCNN 2015 : International Joint Conference on Neural Networks (2015), | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Musical note recognition | es |
dc.subject | Convolutional spiking network | es |
dc.subject | Neuromorphic auditory hardware | es |
dc.subject | Address-event-representation | es |
dc.title | Musical notes classification with Neuromorphic Auditory System using FPGA and a Convolutional Spiking Network | es |
dc.type | info:eu-repo/semantics/conferenceObject | es |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Arquitectura y Tecnología de Computadores | es |
dc.relation.projectID | TEC2012-37868-C04-02 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/7280619 | es |
dc.identifier.doi | 10.1109/IJCNN.2015.7280619 | es |
dc.contributor.group | Universidad de Sevilla. TEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitación | es |
idus.format.extent | 7 | es |
dc.eventtitle | IJCNN 2015 : International Joint Conference on Neural Networks | es |
dc.eventinstitution | Killarney, Ireland | es |
dc.relation.publicationplace | New York, USA | es |