dc.creator | Jiménez Fernández, Ángel Francisco | es |
dc.creator | Cerezuela Escudero, Elena | es |
dc.creator | Miró Amarante, María Lourdes | es |
dc.creator | Domínguez Morales, Manuel Jesús | es |
dc.creator | Gómez Rodríguez, Francisco de Asís | es |
dc.creator | Linares Barranco, Alejandro | es |
dc.creator | Jiménez Moreno, Gabriel | es |
dc.date.accessioned | 2019-07-08T09:03:55Z | |
dc.date.available | 2019-07-08T09:03:55Z | |
dc.date.issued | 2017 | |
dc.identifier.citation | Jiménez 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.issn | 2162-237X | es |
dc.identifier.uri | https://hdl.handle.net/11441/87909 | |
dc.description.abstract | This 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.sponsorship | Ministerio de Economía y Competitividad TEC2012-37868-C04-02 | es |
dc.description.sponsorship | Junta de Andalucía P12-TIC-1300 | es |
dc.format | application/pdf | es |
dc.language.iso | eng | es |
dc.publisher | IEEE Computer Society | es |
dc.relation.ispartof | IEEE Transactions on Neural Networks and Learning Systems, 28 (4), 804-818. | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Address event | es |
dc.subject | Artificial cochlea | es |
dc.subject | FPGA | es |
dc.subject | Neuromorphic engineering | es |
dc.subject | Pulse frequency modulation (PFM) | es |
dc.subject | Real-time audition | es |
dc.title | A Binaural Neuromorphic Auditory Sensor for FPGA: A Spike Signal Processing Approach | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
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.projectID | P12-TIC-1300 | es |
dc.relation.publisherversion | https://ieeexplore.ieee.org/document/7523402 | es |
dc.identifier.doi | 10.1109/TNNLS.2016.2583223 | es |
dc.contributor.group | Universidad de Sevilla. TEP-108: Robótica y Tecnología de Computadores Aplicada a la Rehabilitación | |
idus.format.extent | 14 | es |
dc.journaltitle | IEEE Transactions on Neural Networks and Learning Systems | es |
dc.publication.volumen | 28 | es |
dc.publication.issue | 4 | es |
dc.publication.initialPage | 804 | es |
dc.publication.endPage | 818 | es |
dc.identifier.sisius | 21292096 | es |