Inverse scattering theory is a major theme of applied mathematics, and has applications to such diverse areas as medical imaging, geophysical exploration, and nondestructive testing. The inverse scattering problem is nonlinear and ill-posed, thus presenting particular problems in the development of efficient inversion algorithms. Initial efforts to address these problems focused on nonlinear optimization methods, which required strong a priori information. This led to a qualitative approach to inverse scattering theory in which the amount of a priori information is drastically reduced, although at the expense of only obtaining limited information about the values of constitutive parameters. This book provides an introduction to this important new direction in inverse scattering theory. Beginning with a basic introduction to the theory, the authors proceed to more recent developments, including a detailed discussion of the transmission eigenvalue problem. Both the new generalized linear sampling method and well-known linear sampling and factorization methods are included.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Fioralba Cakoni is a professor in the Department of Mathematics at Rutgers University, New Jersey. She is coauthor of A Qualitative Approach to Inverse Scattering Theory (with David Colton, 2014).
David Colton is a professor in the Department of Mathematical Sciences at the University of Delaware, where he was appointed Unidel Professor in 1996. He is coauthor of A Qualitative Approach to Inverse Scattering Theory (with Fioralba Cakoni, 2014) and Inverse Acoustic and Electromagnetic Scattering Theory, 3rd edition (with Rainer Kress, 2013).
Houssem Haddar is Director of Research at the Institut National de Recherche en Informatique et en Automatique (INRIA), Rocquencourt and a part-time Professor at École Polytechnique, Paris. He is a coauthor of Computational Electromagnetism (with with Ralf Hiptmair, Peter Monk and Rodolfo Rodriguez, 2015).
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Paperback. Etat : New. Inverse scattering theory is a major theme of applied mathematics, and it has applications to such diverse areas as medical imaging, geophysical exploration, and nondestructive testing. The inverse scattering problem is both nonlinear and ill-posed, thus presenting particular problems in the development of efficient inversion algorithms. Although linearized models continue to play an important role in many applications, an increased need to focus on problems in which multiple scattering effects cannot be ignored has led to a central role for nonlinearity, and the possibility of collecting large amounts of data over limited regions of space means that the ill-posed nature of the inverse scattering problem has become a problem of central importance.Initial efforts to address the nonlinear and the ill-posed nature of the inverse scattering problem focused on nonlinear optimization methods. While efficient in many situations, strong a priori information is necessary for their implementation. This problem led to a qualitative approach to inverse scattering theory in which the amount of a priori information is drastically reduced, although at the expense of only obtaining limited information about the values of the constitutive parameters. This qualitative approach (the linear sampling method, the factorization method, the theory of transmission eigenvalues, etc.) is the theme of this book.The authors:Begin with a basic introduction to the theory, then proceed to more recent developments, including a detailed discussion of the transmission eigenvalue problem.Present the new generalized linear sampling method in addition to the well-known linear sampling and factorization methods.In order to achieve clarification of presentation, focus on the inverse scattering problem for scalar homogeneous media. N° de réf. du vendeur LU-9781611974454
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