Splitting Methods in Communication, Imaging, Science, and Engineering / edited by Roland Glowinski, Stanley J. Osher, Wotao Yin.

Format:

Book

Contributor:

Glowinski, Roland., Editor.

Osher, Stanley J., Editor.

Yin, Wotao., Editor.

Series:

Scientific Computation, 1434-8322

Language:

English

Subjects (All):

Computer science--Mathematics.

Computer science.

Optical data processing.

Physics.

Mathematical optimization.

Computational Mathematics and Numerical Analysis.

Image Processing and Computer Vision.

Numerical and Computational Physics, Simulation.

Optimization.

Local Subjects:

Computational Mathematics and Numerical Analysis.

Image Processing and Computer Vision.

Numerical and Computational Physics, Simulation.

Optimization.

Physical Description:

1 online resource (822 pages).

Edition:

1st ed. 2016.

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2016.

Summary:

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. .

Contents:

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

Application of Operator Splitting Methods in Finance

A Numerical Method to Solve Multi-marginal Optimal Transport Problems with Coulomb Cost

Robust Split-step Fourier Methods for Simulating the Propagation of Ultra-short Pulses in Single- and Two-mode Optical Communication Fibers

Operator Splitting Methods with Error Estimator and Adaptive Time-stepping: Application to the Simulation of Combustion Phenomena

Operator Splitting Algorithms for Free Surface Flows: Application to Extrusion Processes

An Operator Splitting Approach to the Solution of Fluid-structure Interaction Problems with Hemodynamics

On Circular cluster Formation in a Rotating Suspension of Non-Brownian Settling Particles in a Fully Filled Circular Cylinder: An Operator Splitting Approach to the Numerical Simulation.

Notes:

Includes bibliographical references at the end of each chapters and index.