Fast algorithms for exponential data modeling

Authors:
H. Park;S. Van Huffel;L. Elden
Affiliations:
Dept. of Comput. Sci., Minnesota Univ., Minneapolis, MN, USA;Lab. des Signaux et Syst., CNRS, Gif-sur-Yvette, France;Lab. des Signaux et Syst., CNRS, Gif-sur-Yvette, France
Venue:
ICASSP '94 Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04
Year:
1994

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Cited 1

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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.