By David M. F. Chapman (auth.), Michael I. Taroudakis, George N. Makrakis (eds.)

ISBN-10: 1441929207

ISBN-13: 9781441929204

ISBN-10: 1475735200

ISBN-13: 9781475735208

Inverse difficulties have a protracted heritage in acoustics, optics, electromagnetics and geophysics, yet only in the near past have the signs supplied by means of ocean acoustic sensors turn into a variety of and complicated sufficient to permit for practical identity of the sea parameters. Acoustic indications propagating for lengthy distances within the water column and reflections of underwater sound from the sea limitations offer novel difficulties of interpretation and inversion.
The chapters during this quantity talk about a number of the modern facets of those difficulties. they supply contemporary and helpful effects for backside acceptance, inverse scattering in acoustic wave publications, and ocean acoustic tomography, in addition to a dialogue of a few of the hot algorithms, resembling these regarding matched-field processing, that experience lately been used for inverting experimental information. every one bankruptcy is by way of a famous professional within the box and represents the cutting-edge. The chapters have all been edited to supply a uniform layout and point of presentation.

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Monte Carlo sampling of solutions to inverse problems. J. Geophys. , 100:12431-12447, 1995. H. Rothman. Nonlinear inversion, statistical mechanics and residual static corrections. Geophysics, 50:2784-2796, 1985. Y. Rubinstein. Simulation and the Monte Carlo Method. Wiley, New York,1981. K. Stoffa. Nonlinear one-dimensional seismic waveform inversion using simulated annealing. Geophysics, 56:1624-1638, 1991. K. Sen and PL Stoffa. Bayesian inference, Gibbs sampier and uncertainty estimation in geophysical inversion.

05 : ,e. 35 r-r-'--~-~--~-------, .. ,. 25 ~. 15 .... 1:' ~ ... - .. 05 ... ~-J:IJ.. 80 c c .. ~ . 40 . , ,. 60 -; tii .. ;. . . . l.. --1. . 6. 5 expressed in the original coordinates. 05, This result implies a more efficient sampling process that has produced a faster convergence ofthe marginal parameter density distributions. 7. It can be seen that the low-energy valleys were exhaustively samp led (cases (a)-(d)) independent of their orien tation with respect to the coordina te axes. Given this thorough sampling, the freeze bath in the rotated coordinates has provided considera ble insight into the structure of the parameter space.

3 Parameter Uncertainty Estimation In an optimization method, emphasis is put on the search for the global minimum of amisfit function. Generally, no attempt is made to estimate the structure of this minimum, or possible local minima in other regions of the model space. For example, in the classical optimization problem of the traveling salesman the goal is to find the shortest route that connects a number of places to be visited by the salesman. The existence of other routes nearly as short is not of much interest.

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Inverse Problems in Underwater Acoustics by David M. F. Chapman (auth.), Michael I. Taroudakis, George N. Makrakis (eds.)


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