DocumentCode :
876408
Title :
Fast orthogonalization algorithm and parallel architecture for AR spectral estimation based on forward-backward linear prediction
Author :
Liu, K. J Ray ; Hsieh, S.F.
Author_Institution :
Dept. of Electr. Eng., Maryland Univ., College Park, MD, USA
Volume :
41
Issue :
3
fYear :
1993
fDate :
3/1/1993 12:00:00 AM
Firstpage :
1453
Lastpage :
1458
Abstract :
Truncated QR methods have been shown to be comparable to SVD-based methods for the sinusoidal frequency estimation based on the forward-backward linear prediction (FBLP) model. However, without exploiting the special structure of the FBLP matrix, the QR decomposition (QRD) of the FBLP matrix has a computational complexity on the order of 2(6m-n)n2/3+O(n 2) for a 2m×n FBLP matrix. A fast algorithm to perform the QRD of the FBLP matrix by exploiting its special Toeplitz-Hankel form is proposed. The computational complexity is reduced to 10n2+4mn+O(n). The fast algorithm can also be easily implemented by a linear systolic array, reducing the number of time steps required to 2m+5n-4
Keywords :
computational complexity; filtering and prediction theory; parallel architectures; spectral analysis; AR spectral estimation; FBLP matrix; QR decomposition; QRD; SVD; Toeplitz-Hankel form; computational complexity; fast orthogonalization algorithm; forward-backward linear prediction; linear systolic array; parallel architecture; sinusoidal frequency estimation; time steps; truncated QR methods; Computational complexity; Extrapolation; Frequency estimation; Iterative algorithms; Matrix decomposition; Parallel architectures; Signal processing; Signal processing algorithms; Signal restoration; Speech processing;
fLanguage :
English
Journal_Title :
Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1053-587X
Type :
jour
DOI :
10.1109/78.205755
Filename :
205755
Link To Document :
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