DocumentCode
3524119
Title
Using the Pearson correlation coefficient to develop an optimally weighted cross relation based blind SIMO identification algorithm
Author
Huang, Yiteng ; Benesty, Jacob ; Chen, Jingdong
Author_Institution
WeVoice, Inc., Bridgewater, NJ
fYear
2009
fDate
19-24 April 2009
Firstpage
3153
Lastpage
3156
Abstract
Blind SIMO identification is challenging when additive noise is strong and for ill-conditioned/acoustic SIMO systems. A weighted cross relation (CR) algorithm presumably can be robust to noise but there lacks a practical way to define the weights. In this paper, the Pearson correlation coefficient (PCC) is used to develop an optimally weighted CR algorithm, which is validated by simulations.
Keywords
acoustic signal processing; blind source separation; correlation methods; noise; Pearson correlation coefficient; acoustic SIMO system; additive noise; blind SIMO identification algorithm; ill-conditioned system; weighted cross relation algorithm; Acoustic noise; Additive noise; Chromium; Finite impulse response filter; Jacobian matrices; Microphones; Noise robustness; Signal processing; Speech; Statistics; Pearson correlation coefficient; Weighted cross relations; acoustic SIMO system; blind identification;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location
Taipei
ISSN
1520-6149
Print_ISBN
978-1-4244-2353-8
Electronic_ISBN
1520-6149
Type
conf
DOI
10.1109/ICASSP.2009.4960293
Filename
4960293
Link To Document