Please use this identifier to cite or link to this item:
logo share SHARE BASE
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE

Artificial neural network algorithms for active noise control applications

AuthorsFernández, Alejandro; Cobo, Pedro
KeywordsActive Noise Control Systems (ANC) (ANC) systems
Artificial neural networks
Real-time systems
Issue DateSep-2002
PublisherSociedad Española de Acústica
CitationForum Acusticum Sevilla 2002. Electro-Acoustics and Instrumentation ; ELE-01-010
AbstractThis paper shows the use of several methods commonly applied to training Artificial Neural Networks (ANN) in Active Noise Control (ANC) systems. Although ANN are usually focused on off-line training, real-time systems can take advantage of modern microprocessors in order to use these techniques. A theoretical study of which of these methods suit best in ANC systems is presented. The results of several simulations will show their effectiveness.
Description6 pages, 5 figures.-- PACS nr.: 43.50 Ki.-- Communication presented at: Forum Acusticum Sevilla 2002 (Sevilla, Spain, 16-20 Sep 2002), comprising: 3rd European Congress on Acoustics; XXXIII Spanish Congress on Acoustics (TecniAcústica 2002); European and Japanese Symposium on Acoustics; 3rd Iberian Congress on Acoustics.-- Special issue of the journal Revista de Acústica, Vol. XXXIII, year 2002.
Appears in Collections:(IA) Comunicaciones congresos

Files in This Item:
File Description SizeFormat
ele01010.pdf340,67 kBAdobe PDFThumbnail
Show full item record
Review this work

Page view(s)

checked on May 26, 2022


checked on May 26, 2022

Google ScholarTM



WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.