DocumentCode :
1354045
Title :
Hybrid Newton/Gauss-Newton algorithm for time-domain analysis of A/D converters
Author :
Haddadi, Djamel ; Dallet, Dominique ; Marchegay, Philippe
Author_Institution :
Lab. IXL-ENSERB, Bordeaux I Univ., Talence, France
Volume :
47
Issue :
7
fYear :
2000
fDate :
7/1/2000 12:00:00 AM
Firstpage :
655
Lastpage :
659
Abstract :
This brief describes a maximum-likelihood estimator for a sum of harmonically related sinewaves for characterizing analog-to-digital (A/D) converters. The frequency is estimated by means of the Newton method. For the iterations where singularity problems occur, the algorithm switches to the Gauss-Newton method combined with the singular value decomposition. The initial frequency accuracy required by this algorithm is determined and the algorithm is modified in order to converge to the global minimum, whatever the initial frequency uncertainty. Thus, one can use the frequencies of the signal generators to provide the starting value. Once the frequency is determined, the linear parameters of the model are estimated by solving a linear set of equations. It is shown through simulation and experimental results that the proposed algorithm is fast, accurate, and robust, with respect to the initial guess of the frequency
Keywords :
Newton method; analogue-digital conversion; iterative methods; maximum likelihood estimation; singular value decomposition; time-domain analysis; A/D converters; frequency accuracy; harmonically related sinewaves; hybrid Newton/Gauss-Newton algorithm; initial frequency uncertainty; initial guess; iterations; linear parameters; maximum-likelihood estimator; singular value decomposition; singularity problems; starting value; time-domain analysis; Analog-digital conversion; Frequency estimation; Least squares methods; Maximum likelihood estimation; Newton method; Recursive estimation; Singular value decomposition; Switches; Time domain analysis; Uncertainty;
fLanguage :
English
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1057-7130
Type :
jour
DOI :
10.1109/82.850424
Filename :
850424
Link To Document :
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