Titlebook: Optimization and Regularization for Computational Inverse Problems and Applications; Yanfei Wang,Changchun Yang,Anatoly G. Yagola Book 201

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Modified Regularization Scheme with Application in Reconstructing Neumann-Dirichlet Mappingroblem of reconstructing the Neumann-Dirichlet mapping from the discrete Neumann and Dirichlet data. The Neumann-Dirichlet mappings are used widely in the studying of inverse problems for partial differential equations.

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Book 2011with practical applications, particularly emphasizing the combination of optimization and regularization for solving inverse problems. This book covers both the methods, including standard regularization theory, Fejer processes for linear and nonlinear problems, the balancing principle, extrapolated

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Convergence Analysis of Nonlinear Conjugate Gradient Methodsor these methods under mild assumptions. In addition, an analysis is also given to a new conjugate gradient method, which further demonstrates the usefulness of the condition and the new property. Some discussions about the bound in the hybrid conjugate gradient methods are also given.

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Location across Disciplines: Reflections on the CSISS Experience,xperiences of CSISS offer guidance on broad-based dissemination efforts across disciplines and for future initiatives on the basic concepts of spatial thinking. A suggested set of concepts is proposed as a basis for augmenting knowledge in diverse fields through applications of spatial thinking and

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L-M,round for easy identification and advancd material is marked with an asterisk. .The book is intended to be self-contained. No previous knowledge of multi-sensor data fusion is assumed, although some familarity 978-3-642-43730-4978-3-642-27222-6

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