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Full-Text Articles in Physical Sciences and Mathematics

A Sensitivity Matrix Methodology For Inverse Problem Formulation, Ariel Cintron-Arias, H. T. Banks, Alex Capaldi, Alun L. Lloyd Jul 2009

A Sensitivity Matrix Methodology For Inverse Problem Formulation, Ariel Cintron-Arias, H. T. Banks, Alex Capaldi, Alun L. Lloyd

Alex Capaldi

We propose an algorithm to select parameter subset combinations that can be estimated using an ordinary least-squares (OLS) inverse problem formulation with a given data set. First, the algorithm selects the parameter combinations that correspond to sensitivity matrices with full rank. Second, the algorithm involves uncertainty quantification by using the inverse of the Fisher Information Matrix. Nominal values of parameters are used to construct synthetic data sets, and explore the effects of removing certain parameters from those to be estimated using OLS procedures. We quantify these effects in a score for a vector parameter defined using the norm of the …


A Sensitivity Matrix Methodology For Inverse Problem Formulation, Alex Calpaldi Dec 2008

A Sensitivity Matrix Methodology For Inverse Problem Formulation, Alex Calpaldi

Alex Capaldi

We propose an algorithm to select parameter subset combinations that can be estimated using an ordinary least-squares (OLS) inverse problem formulation with a given data set. First, the algorithm selects the parameter combinations that correspond to sensitivity matrices with full rank. Second, the algorithm involves uncertainty quantification by using the inverse of the Fisher Information Matrix. Nominal values of parameters are used to construct synthetic data sets, and explore the effects of removing certain parameters from those to be estimated using OLS procedures. We quantify these effects in a score for a vector parameter defined using the norm of the …


Asymptotic Accuracy Of Geoacoustic Inversions, Michele Zanolin, Ian Ingram, Aaron Thode, Nicholas C. Makris Sep 2004

Asymptotic Accuracy Of Geoacoustic Inversions, Michele Zanolin, Ian Ingram, Aaron Thode, Nicholas C. Makris

Michele Zanolin

Criteria necessary to accurately estimate a set of unknown geoacoustic parameters from remote acoustic measurements are developed in order to aid the design of geoacoustic experiments. The approach is to have estimation error fall within a specified design threshold by adjusting controllable quantities such as experimental sample size or signal-to-noise ratio (SNR). This is done by computing conditions on sample size and SNR necessary for any estimate to have a variance that (1) asymptotically attains the Cramer–Rao lower bound (CRLB) and (2) has a CRLB that falls within the specified design error threshold. Applications to narrow band deterministic signals received …