Analysis of source separation algorithms in industrial acoustic environments

This paper shows the results from the computation cost evaluation of three blind source separation algorithms. The algorithms tested were: FastICA, Adaptive Algorithm Based on Natural Gradient, and Adaptive EASI Based on Relative Gradient. The algorithms were chosen for their relative simplicity, an...

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Autores Principales: Lozano, Clevis, Gómez, Andrés, Chacón-Rodríguez, Alfonso, Merchán, Fernando, Julián, Pedro
Formato: Objeto de conferencia
Idioma: Inglés
Publicado: Institute of Electrical and Electronics Engineers Inc. 2017
Materias:
Acceso en línea: https://www.scopus.com/inward/record.url?eid=2-s2.0-84945156117&partnerID=40&md5=72998182186ff5845045de39e1c40ab7
https://hdl.handle.net/2238/6943
Sumario: This paper shows the results from the computation cost evaluation of three blind source separation algorithms. The algorithms tested were: FastICA, Adaptive Algorithm Based on Natural Gradient, and Adaptive EASI Based on Relative Gradient. The algorithms were chosen for their relative simplicity, and taking into account their hardware implementation feasibility, either on a FPGA or an ASIC, as part of a system for acoustic localization of mobile agents in industrial environments.