Title :
Fast algorithms for exponential data modeling
Author :
Park, Haesun ; Van Huffel, Sabine ; Eldén, Lors
Author_Institution :
Dept. of Comput. Sci., Minnesota Univ., Minneapolis, MN, USA
Abstract :
A new fast algorithm is presented for quantifying signals modeled by a sum of exponentially damped sinusoids. The new algorithm is applied to the quantitative analysis of Nuclear Magnetic Resonance (NMR) data and is shown to be up to an order of magnitude more efficient than currently used linear prediction and state-space based methods
Keywords :
Hankel matrices; biomedical NMR; exponential distribution; matrix decomposition; medical image processing; parameter estimation; Hankel structure; NMR data; exponential data modeling; exponentially damped sinusoids; fast algorithms; linear prediction; state-space based methods; Algorithm design and analysis; Computer science; Frequency estimation; Laboratories; Least squares methods; Magnetic analysis; Mathematics; Matrix decomposition; Nuclear magnetic resonance; Parameter estimation;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-1775-0
DOI :
10.1109/ICASSP.1994.389885
