DocumentCode :
2151142
Title :
Time domain reconstruction of spatial sound fields using compressed sensing
Author :
Wabnitz, Andrew ; Epain, Nicolas ; Van Schaik, André ; Jin, Craig
Author_Institution :
Comput. & Audio Res. Lab. (CARLab), Univ. of Sydney, Sydney, NSW, Australia
fYear :
2011
fDate :
22-27 May 2011
Firstpage :
465
Lastpage :
468
Abstract :
A novel technique for time domain spatial sound reproduction using compressed sensing is presented. The presented technique is based on the application of compressed sensing theory, which is used to improve the accuracy of the reconstructed sound field. In addition, singular value decomposition is also applied, which acts to significantly reduce the size of the data set to process, thus making it efficient and realisable for real-time applications. Results are presented from the preliminary performance evaluation of the compressed sensing technique in comparison to the Higher Order Ambisonic reconstruction technique.
Keywords :
acoustic signal processing; signal reconstruction; singular value decomposition; time-domain analysis; compressed sensing; data set; higher order ambisonic reconstruction technique; performance evaluation; singular value decomposition; time domain sound field reconstruction; time domain spatial sound field reproduction; Arrays; Compressed sensing; Harmonic analysis; Image reconstruction; Loudspeakers; Optimization; Receivers; Acoustic signal processing; Optimization; Signal reconstruction; Sparse matrices;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2011 IEEE International Conference on
Conference_Location :
Prague
ISSN :
1520-6149
Print_ISBN :
978-1-4577-0538-0
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2011.5946441
Filename :
5946441
Link To Document :
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