Splitting Methods in Communication, Imaging, Science, and Engineering. 1st ed. 2016

種類:

電子ブック

責任表示:

edited by Roland Glowinski, Stanley J. Osher, Wotao Yin

出版情報:

Cham : Springer International Publishing : Imprint: Springer, 2016

著者名:

• Glowinski, Roland.
• Osher, Stanley J.
• Yin, Wotao.
• SpringerLink (Online service)

シリーズ名:

Scientific Computation ;

ISBN:

9783319415895 [3319415891]    

注記:

Introduction -- Some Facts about Operator-Splitting and Alternating Direction Methods -- Operator Splitting -- Convergence Rate Analysis of Several Splitting Schemes -- Self Equivalence of the Alternating Direction Method of Multipliers -- Application of the Strictly Contractive Peaceman-Rachford Splitting Method to Multi-block Separable Convex Programming -- Nonconvex Sparse Regularization and Splitting Algorithms -- ADMM and Non-convex Variational Problems -- Operator Splitting Methods in Compressive Sensing and Sparse Approximation -- First Order Algorithms in Variational Image Processing -- A Parameter Free ADI-like Method for the Numerical Solution of Large Scale Lyapunov Equations -- Splitting Enables Overcoming the Curse of Dimensionality -- ADMM Algorithmic Regularization Paths for Sparse Statistical Machine Learning -- Decentralized Learning for Wireless Communications and Networking -- Splitting Methods for SPDEs: From Robustness to Financial Engineering, Optimal Control and Nonlinear Filtering -- A
This book is about computational methods based on operator splitting. It consists of twenty-three chapters written by recognized splitting method contributors and practitioners, and covers a vast spectrum of topics and application areas, including computational mechanics, computational physics, image processing, wireless communication, nonlinear optics, and finance. Therefore, the book presents very versatile aspects of splitting methods and their applications, motivating the cross-fertilization of ideas. .

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