DocumentCode :
2174269
Title :
Analysis of source separation algorithms in industrial acoustic environments
Author :
Lozano, Clevis ; Gomez, Andres ; Chacon-Rodriguez, Alfonso ; Merchan, Fernando ; Julian, Pedro
Author_Institution :
DCILab, Escuela de Ingeniería Electrónica, Tecnológico de Costa Rica, Costa Rica
fYear :
2015
fDate :
24-27 Feb. 2015
Firstpage :
1
Lastpage :
4
Abstract :
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.
Keywords :
Acoustics; Adaptive algorithms; Algorithm design and analysis; Blind source separation; Conferences; Microphones; Signal processing algorithms; Adaptive Algorithm Based on Natural Gradient; Adaptive EASI Based on Relative Gradient; Blind Source Separation (BSS); FPGA; FastICA; acoustic localization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Circuits & Systems (LASCAS), 2015 IEEE 6th Latin American Symposium on
Conference_Location :
Montevideo, Uruguay
Type :
conf
DOI :
10.1109/LASCAS.2015.7250482
Filename :
7250482
Link To Document :
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