tailieunhanh - A study of the LCMV and MVDR noise reduction filters

In real-world environments, the signals captured by a set of microphones in a speech communication system are mixtures of the desired signal, interference, and ambient noise. A promising solution for proper speech acquisition (with reduced noise and interference) in this context consists in using the linearly constrained minimum variance (LCMV) beamformer to reject the interference, reduce the overall mixture energy, and preserve the target signal. The minimum variance distortionless response beamformer (MVDR) is also commonly known to reduce the interferenceplus-noise energy without distorting the desired signal. | IEEE TRANSACTIONS ON SIGNAL PROCESSING VOL. 58 NO. 9 SEPTEMBER 2010 4925 6 W. S. Cleveland Robust locally weighted regression and smoothing scatterplots J. Amer. Stat. Assoc. vol. 74 pp. 829-836 1979. 7 S. A. Cruces-Alvarez A. Cichocki and S. Amari From blind signal extraction to blind instantaneous signal separation Criteria algorithms and stability ỈEEE Trans. Neural Netw. vol. 15 no. 4 pp. 859-873 Jul. 2004. 8 W. De Clercq A. Vergult B. Vanrumste W. Van Paesschen and S. Van Huffel Canonical correlation analysis applied to remove muscle artifacts from the electroencephalogram ỈEEE Trans. Biomed. Eng. vol. 53 no. 12 pp. 2583-2587 Dec. 2006. 9 B. De Moor Daisy Database for the Identification of Systems. Online . Available http sista daisy 10 D. H. Foley Considerations of sample and feature size ỈEEE Trans. Inf. Theory vol. IT-18 no. 5 pp. 618-626 Sep. 1972. 11 O. Friman M. Borga P. Lundberg and H. Knutsson Exploratory fMRI analysis by autocorrelation maximization NeuroỈmage vol. 16 no. 2 pp. 454-464 2002. 12 A. Green M. Berman P. Switzer and M. Craig A transformation for ordering multispectral data in terms of image quality with implications for noise removal ỈEEE Trans. Geosci. Remote Sens. vol. 26 no. 1 pp. 65-74 Jan. 1988. 13 D. R. Hundley M. J. Kirby and M. Anderle Blind source separation using the maximum signal fraction approach Signal Process. vol. 82 pp. 1505-1508 2002. 14 A. Hyvărinen J. Karhunen and E. Oja Independent ComponenlAnal-ysis. New York Wiley 2001. 15 A. Hyvărinen Fast and robust fixed-point algorithms for independent component analysis ỈEEE Trans. Neural Netw. vol. 10 no. 3 pp. 626-634 May 1999. 16 EEG Pattern Analysis Comp. Sci. Dept. Colorado State Univ. Ft. Collins CO Online . Available http eeg 17 Y. Koren and L. Carmel Robust linear dimensionality reduction ỈEEE Trans. Vis. Comput. Graph. vol. 10 no. 4 pp. 459-470 Jul. Aug. 2004. 18 . Lee M. Girolami and T. Sejnowski Independent component .