Max Linear Systems Theory And Algorithms
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Max Linear Systems Theory And Algorithms
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Author : Peter Butkovič
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-08-05
Max Linear Systems Theory And Algorithms written by Peter Butkovič and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-08-05 with Mathematics categories.
Recent years have seen a significant rise of interest in max-linear theory and techniques. Specialised international conferences and seminars or special sessions devoted to max-algebra have been organised. This book aims to provide a first detailed and self-contained account of linear-algebraic aspects of max-algebra for general (that is both irreducible and reducible) matrices. Among the main features of the book is the presentation of the fundamental max-algebraic theory (Chapters 1-4), often scattered in research articles, reports and theses, in one place in a comprehensive and unified form. This presentation is made with all proofs and in full generality (that is for both irreducible and reducible matrices). Another feature is the presence of advanced material (Chapters 5-10), most of which has not appeared in a book before and in many cases has not been published at all. Intended for a wide-ranging readership, this book will be useful for anyone with basic mathematical knowledge (including undergraduate students) who wish to learn fundamental max-algebraic ideas and techniques. It will also be useful for researchers working in tropical geometry or idempotent analysis.
Max Linear Systems
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Author : Peter Butkovi
language : en
Publisher:
Release Date : 2010-09-13
Max Linear Systems written by Peter Butkovi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-13 with categories.
Iterative Methods For Linear Systems
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Author : Maxim A. Olshanskii
language : en
Publisher: SIAM
Release Date : 2014-07-21
Iterative Methods For Linear Systems written by Maxim A. Olshanskii and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-21 with Mathematics categories.
Iterative Methods for Linear Systems?offers a mathematically rigorous introduction to fundamental iterative methods for systems of linear algebraic equations. The book distinguishes itself from other texts on the topic by providing a straightforward yet comprehensive analysis of the Krylov subspace methods, approaching the development and analysis of algorithms from various algorithmic and mathematical perspectives, and going beyond the standard description of iterative methods by connecting them in a natural way to the idea of preconditioning.??
Optimal Control Of Nonlinear Parabolic Systems
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Author : Pekka Neittaanmaki
language : en
Publisher: CRC Press
Release Date : 1994-02-08
Optimal Control Of Nonlinear Parabolic Systems written by Pekka Neittaanmaki and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1994-02-08 with Mathematics categories.
This book discusses theoretical approaches to the study of optimal control problems governed by non-linear evolutions - including semi-linear equations, variational inequalities and systems with phase transitions. It also provides algorithms for solving non-linear parabolic systems and multiphase Stefan-like systems.
Theory And Algorithms For Linear Optimization
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Author : Cornelis Roos
language : en
Publisher:
Release Date : 1997-03-04
Theory And Algorithms For Linear Optimization written by Cornelis Roos and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997-03-04 with Mathematics categories.
The approach to LO in this book is new in many aspects. In particular the IPM based development of duality theory is surprisingly elegant. The algorithmic parts of the book contain a complete discussion of many algorithmic variants, including predictor-corrector methods, partial updating, higher order methods and sensitivity and parametric analysis.
Linear Programming Mathematics Theory And Algorithms
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Author : M.J. Panik
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-01
Linear Programming Mathematics Theory And Algorithms written by M.J. Panik and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-01 with Mathematics categories.
Linear Programming provides an in-depth look at simplex based as well as the more recent interior point techniques for solving linear programming problems. Starting with a review of the mathematical underpinnings of these approaches, the text provides details of the primal and dual simplex methods with the primal-dual, composite, and steepest edge simplex algorithms. This then is followed by a discussion of interior point techniques, including projective and affine potential reduction, primal and dual affine scaling, and path following algorithms. Also covered is the theory and solution of the linear complementarity problem using both the complementary pivot algorithm and interior point routines. A feature of the book is its early and extensive development and use of duality theory. Audience: The book is written for students in the areas of mathematics, economics, engineering and management science, and professionals who need a sound foundation in the important and dynamic discipline of linear programming.
Linear Systems Theory
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Author : Ferenc Szidarovszky
language : en
Publisher: Springer
Release Date : 1992-02-21
Linear Systems Theory written by Ferenc Szidarovszky and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992-02-21 with Mathematics categories.
Linear Systems Theory is a comprehensive text that presents a mathematically rigorous development of important tools of linear systems theory. These tools include differential and difference equations, Laplace and Z transforms, state space and transfer function representations, stability, controllability and observability, duality, canonical forms, realizability, minimal realizations, observers, feedback compensators, nonnegative systems, Kalman filters, and adaptive control and neural networks.
Optimization And Control Of Bilinear Systems
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Author : Panos M. Pardalos
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-14
Optimization And Control Of Bilinear Systems written by Panos M. Pardalos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-14 with Science categories.
Covers developments in bilinear systems theory Focuses on the control of open physical processes functioning in a non-equilibrium mode Emphasis is on three primary disciplines: modern differential geometry, control of dynamical systems, and optimization theory Includes applications to the fields of quantum and molecular computing, control of physical processes, biophysics, superconducting magnetism, and physical information science
Sparse Solutions Of Underdetermined Linear Systems And Their Applications
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Author : Ming-Jun Lai
language : en
Publisher: SIAM
Release Date : 2021-06-25
Sparse Solutions Of Underdetermined Linear Systems And Their Applications written by Ming-Jun Lai and has been published by SIAM this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-25 with Mathematics categories.
This textbook presents a special solution to underdetermined linear systems where the number of nonzero entries in the solution is very small compared to the total number of entries. This is called a sparse solution. Since underdetermined linear systems can be very different, the authors explain how to compute a sparse solution using many approaches. Sparse Solutions of Underdetermined Linear Systems and Their Applications contains 64 algorithms for finding sparse solutions of underdetermined linear systems and their applications for matrix completion, graph clustering, and phase retrieval and provides a detailed explanation of these algorithms including derivations and convergence analysis. Exercises for each chapter help readers understand the material. This textbook is appropriate for graduate students in math and applied math, computer science, statistics, data science, and engineering. Advisors and postdoctoral scholars will also find the book interesting and useful.
Sparse Optimization Theory And Methods
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Author : Yun-Bin Zhao
language : en
Publisher: CRC Press
Release Date : 2018-07-04
Sparse Optimization Theory And Methods written by Yun-Bin Zhao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-04 with Business & Economics categories.
Seeking sparse solutions of underdetermined linear systems is required in many areas of engineering and science such as signal and image processing. The efficient sparse representation becomes central in various big or high-dimensional data processing, yielding fruitful theoretical and realistic results in these fields. The mathematical optimization plays a fundamentally important role in the development of these results and acts as the mainstream numerical algorithms for the sparsity-seeking problems arising from big-data processing, compressed sensing, statistical learning, computer vision, and so on. This has attracted the interest of many researchers at the interface of engineering, mathematics and computer science. Sparse Optimization Theory and Methods presents the state of the art in theory and algorithms for signal recovery under the sparsity assumption. The up-to-date uniqueness conditions for the sparsest solution of underdertemined linear systems are described. The results for sparse signal recovery under the matrix property called range space property (RSP) are introduced, which is a deep and mild condition for the sparse signal to be recovered by convex optimization methods. This framework is generalized to 1-bit compressed sensing, leading to a novel sign recovery theory in this area. Two efficient sparsity-seeking algorithms, reweighted l1-minimization in primal space and the algorithm based on complementary slackness property, are presented. The theoretical efficiency of these algorithms is rigorously analysed in this book. Under the RSP assumption, the author also provides a novel and unified stability analysis for several popular optimization methods for sparse signal recovery, including l1-mininization, Dantzig selector and LASSO. This book incorporates recent development and the author’s latest research in the field that have not appeared in other books.