Search Results - "Dosso, SE"

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  1. 1

    Quantifying uncertainty in geoacoustic inversion. I. A fast Gibbs sampler approach by Dosso, Stan E

    “…This paper develops a new approach to estimating seabed geoacoustic properties and their uncertainties based on a Bayesian formulation of matched-field…”
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    Journal Article
  2. 2

    Bayesian multiple-source localization in an uncertain ocean environment by Dosso, Stan E., Wilmut, Michael J.

    “…This paper considers simultaneous localization of multiple acoustic sources when properties of the ocean environment (water column and seabed) are poorly…”
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    Journal Article
  3. 3

    Session 3aUW Underwater Acoustics, Acoustical Oceanography, and Signal Processing in Acoustics: Inversion Methods and Uncertainty Estimation in Ocean Environments by Dosso, SE, Knobles, D P

    “…Insufficient sampling in frequency domain results in range aliasing that affect geoacoustic inversion. Range aliasing and its effects on source localization…”
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  4. 4

    Model selection and Bayesian inference for high-resolution seabed reflection inversion by Dettmer, Jan, Dosso, Stan E., Holland, Charles W.

    “…This paper applies Bayesian inference, including model selection and posterior parameter inference, to inversion of seabed reflection data to resolve sediment…”
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  5. 5

    Bayesian geoacoustic inversion of ship noise on a horizontal array by Tollefsen, Dag, Dosso, Stan E.

    “…This paper applies geoacoustic inversion to low-frequency narrow-band acoustic data from a quiet surface ship recorded on a bottom-moored horizontal line array…”
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  6. 6

    Sequential trans-dimensional Monte Carlo for range-dependent geoacoustic inversion by Dettmer, Jan, Dosso, Stan E, Holland, Charles W

    “…This paper develops a sequential trans-dimensional Monte Carlo algorithm for geoacoustic inversion in a strongly range-dependent environment. The algorithm…”
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    Journal Article
  7. 7

    Crustal anisotropy in the forearc of the Northern Cascadia Subduction Zone, British Columbia by Balfour, N. J., Cassidy, J. F., Dosso, S. E.

    Published in Geophysical journal international (01-01-2012)
    “…SUMMARY This paper aims to identify sources and variations of crustal anisotropy from shear‐wave splitting measurements in the forearc of the Northern Cascadia…”
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  8. 8

    Comparison of focalization and marginalization for Bayesian tracking in an uncertain ocean environment by Dosso, Stan E., Wilmut, Michael J.

    “…This paper compares focalization and marginalization approaches to source tracking when uncertain ocean environmental parameters are included, in addition to…”
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    Journal Article
  9. 9

    Bayesian evidence computation for model selection in non-linear geoacoustic inference problems by Dettmer, Jan, Dosso, Stan E., Osler, John C.

    “…This paper applies a general Bayesian inference approach, based on Bayesian evidence computation, to geoacoustic inversion of interface-wave dispersion data…”
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  10. 10

    Trans-dimensional geoacoustic inversion by Dettmer, J, Dosso, SE, Holland, C W

    “…This paper develops a general trans-dimensional Bayesian methodology for geoacoustic inversion. Trans-dimensional inverse problems are a generalization of…”
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    Journal Article
  11. 11

    Data error covariance in matched-field geoacoustic inversion by DOSSO, Stan E, NIELSEN, Peter L, WILMUT, Michael J

    “…Many approaches to geoacoustic inversion are based implicitly on the assumptions that data errors are Gaussian-distributed and spatially uncorrelated (i.e.,…”
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  12. 12

    Quantifying ocean acoustic sensitivity to environmental uncertainty/variability by Dosso, Stan E.

    “…It is well known that acoustic data used in sonar applications are strongly influenced by physical parameters of the ocean environment. Environmental…”
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  13. 13

    Three-dimensional source tracking in an uncertain environment via Bayesian marginalization by Tollefsen, Dag, Dosso, Stan E.

    “…This paper develops a non-linear Bayesian marginalization approach for three-dimensional source tracking in shallow water with uncertain environmental…”
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  14. 14

    Quantifying uncertainty in geoacoustic inversion. II. Application to broadband, shallow-water data by Dosso, Stan E., Nielsen, Peter L.

    “…This paper applies the new method of fast Gibbs sampling (FGS) to estimate the uncertainties of seabed geoacoustic parameters in a broadband, shallow-water…”
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  15. 15

    Bayesian source tracking in an uncertain ocean environment by Dosso, Stan E., Wilmut, Michael J.

    “…This paper considers matched-field tracking of a moving acoustic source when properties of the ocean environment (water column and seabed) are poorly known…”
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    Journal Article
  16. 16

    Bayesian tracking predictions in an uncertain ocean environment by Dosso, Stan E., Wilmut, Michael J.

    “…This paper considers probabilistic prediction of the future locations of a moving acoustic source in the ocean based on past locations as determined by…”
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  17. 17

    Data Uncertainty Estimation in Matched-Field Geoacoustic Inversion by Dosso, S.E., Wilmut, M.J.

    Published in IEEE journal of oceanic engineering (01-04-2006)
    “…This paper examines a variety of approaches to treating unknown data uncertainties in matched-field geoacoustic inversion. Both optimal parameter estimation…”
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  18. 18

    Array element localization using ship noise by Morley, Michael G., Dosso, Stan E., Chapman, N. Ross

    “…This paper describes a method of estimating hydrophone positions in a receiver array using the noise from a passing ship. Relative arrival times of the…”
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  19. 19

    Bayesian source tracking in an uncertain ocean environment by Dosso, Stan E., Wilmut, Michael J.

    “…This paper considers matched-field tracking of a moving acoustic source in the ocean when acoustical properties of the environment (water column and seabed)…”
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  20. 20

    Estimation of seismic velocities of upper oceanic crust from ocean bottom reflection loss data by Dong, Hefeng, Chapman, N Ross, Hannay, David E, Dosso, Stan E

    “…This paper describes a Bayesian inversion of acoustic reflection loss versus angle measurements to estimate the compressional and shear wave velocities in…”
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