Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations

Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations

Author: Ellida M. Khazen

Publisher: Xlibris Corporation

Published: 2009-11-16

Total Pages: 320

ISBN-13: 1462807178

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This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.


Book Synopsis Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations by : Ellida M. Khazen

Download or read book Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations written by Ellida M. Khazen and published by Xlibris Corporation. This book was released on 2009-11-16 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.


Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations

Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations

Author: Ellida M. Khazen

Publisher: Xlibris Corporation

Published: 2009

Total Pages: 320

ISBN-13: 1441557245

DOWNLOAD EBOOK

This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.


Book Synopsis Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations by : Ellida M. Khazen

Download or read book Methods of Optimal Statistical Decisions, Optimal Control, and Stochastic Differential Equations written by Ellida M. Khazen and published by Xlibris Corporation. This book was released on 2009 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the reader with some insight into the mathematical models of random processes with continuous time, stochastic differential equations and stochastic integrals. An advanced development of the mathematical methods of optimal statistical decisions, statistical sequential analysis, and informational estimation of risks, and new methods and solutions to the important problems of the theory of optimal control are presented. The new original results obtained by this author and published shortly in her numerous scientific-research papers are presented in a systematic way in this book. The book is intended for engineers, students, post-graduate students, and scientist researchers. The presentation of the material is accessible to engineers.


Stochastic Optimal Control in Infinite Dimension

Stochastic Optimal Control in Infinite Dimension

Author: Giorgio Fabbri

Publisher: Springer

Published: 2017-06-22

Total Pages: 916

ISBN-13: 3319530674

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Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite dimension. Readers from other fields who want to learn the basic theory will also find it useful. The prerequisites are: standard functional analysis, the theory of semigroups of operators and its use in the study of PDEs, some knowledge of the dynamic programming approach to stochastic optimal control problems in finite dimension, and the basics of stochastic analysis and stochastic equations in infinite-dimensional spaces.


Book Synopsis Stochastic Optimal Control in Infinite Dimension by : Giorgio Fabbri

Download or read book Stochastic Optimal Control in Infinite Dimension written by Giorgio Fabbri and published by Springer. This book was released on 2017-06-22 with total page 916 pages. Available in PDF, EPUB and Kindle. Book excerpt: Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite dimension. Readers from other fields who want to learn the basic theory will also find it useful. The prerequisites are: standard functional analysis, the theory of semigroups of operators and its use in the study of PDEs, some knowledge of the dynamic programming approach to stochastic optimal control problems in finite dimension, and the basics of stochastic analysis and stochastic equations in infinite-dimensional spaces.


Continuous-time Stochastic Control and Optimization with Financial Applications

Continuous-time Stochastic Control and Optimization with Financial Applications

Author: Huyên Pham

Publisher: Springer Science & Business Media

Published: 2009-05-28

Total Pages: 243

ISBN-13: 3540895000

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Stochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other hand, problems in finance have recently led to new developments in the theory of stochastic control. This volume provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality methods. The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc. This book is directed towards graduate students and researchers in mathematical finance, and will also benefit applied mathematicians interested in financial applications and practitioners wishing to know more about the use of stochastic optimization methods in finance.


Book Synopsis Continuous-time Stochastic Control and Optimization with Financial Applications by : Huyên Pham

Download or read book Continuous-time Stochastic Control and Optimization with Financial Applications written by Huyên Pham and published by Springer Science & Business Media. This book was released on 2009-05-28 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: Stochastic optimization problems arise in decision-making problems under uncertainty, and find various applications in economics and finance. On the other hand, problems in finance have recently led to new developments in the theory of stochastic control. This volume provides a systematic treatment of stochastic optimization problems applied to finance by presenting the different existing methods: dynamic programming, viscosity solutions, backward stochastic differential equations, and martingale duality methods. The theory is discussed in the context of recent developments in this field, with complete and detailed proofs, and is illustrated by means of concrete examples from the world of finance: portfolio allocation, option hedging, real options, optimal investment, etc. This book is directed towards graduate students and researchers in mathematical finance, and will also benefit applied mathematicians interested in financial applications and practitioners wishing to know more about the use of stochastic optimization methods in finance.


Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE

Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE

Author: Nizar Touzi

Publisher: Springer Science & Business Media

Published: 2012-09-25

Total Pages: 219

ISBN-13: 1461442869

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This book collects some recent developments in stochastic control theory with applications to financial mathematics. We first address standard stochastic control problems from the viewpoint of the recently developed weak dynamic programming principle. A special emphasis is put on the regularity issues and, in particular, on the behavior of the value function near the boundary. We then provide a quick review of the main tools from viscosity solutions which allow to overcome all regularity problems. We next address the class of stochastic target problems which extends in a nontrivial way the standard stochastic control problems. Here the theory of viscosity solutions plays a crucial role in the derivation of the dynamic programming equation as the infinitesimal counterpart of the corresponding geometric dynamic programming equation. The various developments of this theory have been stimulated by applications in finance and by relevant connections with geometric flows. Namely, the second order extension was motivated by illiquidity modeling, and the controlled loss version was introduced following the problem of quantile hedging. The third part specializes to an overview of Backward stochastic differential equations, and their extensions to the quadratic case.​


Book Synopsis Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE by : Nizar Touzi

Download or read book Optimal Stochastic Control, Stochastic Target Problems, and Backward SDE written by Nizar Touzi and published by Springer Science & Business Media. This book was released on 2012-09-25 with total page 219 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book collects some recent developments in stochastic control theory with applications to financial mathematics. We first address standard stochastic control problems from the viewpoint of the recently developed weak dynamic programming principle. A special emphasis is put on the regularity issues and, in particular, on the behavior of the value function near the boundary. We then provide a quick review of the main tools from viscosity solutions which allow to overcome all regularity problems. We next address the class of stochastic target problems which extends in a nontrivial way the standard stochastic control problems. Here the theory of viscosity solutions plays a crucial role in the derivation of the dynamic programming equation as the infinitesimal counterpart of the corresponding geometric dynamic programming equation. The various developments of this theory have been stimulated by applications in finance and by relevant connections with geometric flows. Namely, the second order extension was motivated by illiquidity modeling, and the controlled loss version was introduced following the problem of quantile hedging. The third part specializes to an overview of Backward stochastic differential equations, and their extensions to the quadratic case.​


Statistical Methods for Stochastic Differential Equations

Statistical Methods for Stochastic Differential Equations

Author: Mathieu Kessler

Publisher: CRC Press

Published: 2012-05-17

Total Pages: 507

ISBN-13: 1439849765

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The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to th


Book Synopsis Statistical Methods for Stochastic Differential Equations by : Mathieu Kessler

Download or read book Statistical Methods for Stochastic Differential Equations written by Mathieu Kessler and published by CRC Press. This book was released on 2012-05-17 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seventh volume in the SemStat series, Statistical Methods for Stochastic Differential Equations presents current research trends and recent developments in statistical methods for stochastic differential equations. Written to be accessible to both new students and seasoned researchers, each self-contained chapter starts with introductions to th


Optimal Control of Partial Differential Equations

Optimal Control of Partial Differential Equations

Author: Andrea Manzoni

Publisher: Springer Nature

Published: 2022-01-01

Total Pages: 507

ISBN-13: 3030772268

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This is a book on optimal control problems (OCPs) for partial differential equations (PDEs) that evolved from a series of courses taught by the authors in the last few years at Politecnico di Milano, both at the undergraduate and graduate levels. The book covers the whole range spanning from the setup and the rigorous theoretical analysis of OCPs, the derivation of the system of optimality conditions, the proposition of suitable numerical methods, their formulation, their analysis, including their application to a broad set of problems of practical relevance. The first introductory chapter addresses a handful of representative OCPs and presents an overview of the associated mathematical issues. The rest of the book is organized into three parts: part I provides preliminary concepts of OCPs for algebraic and dynamical systems; part II addresses OCPs involving linear PDEs (mostly elliptic and parabolic type) and quadratic cost functions; part III deals with more general classes of OCPs that stand behind the advanced applications mentioned above. Starting from simple problems that allow a “hands-on” treatment, the reader is progressively led to a general framework suitable to face a broader class of problems. Moreover, the inclusion of many pseudocodes allows the reader to easily implement the algorithms illustrated throughout the text. The three parts of the book are suitable to readers with variable mathematical backgrounds, from advanced undergraduate to Ph.D. levels and beyond. We believe that applied mathematicians, computational scientists, and engineers may find this book useful for a constructive approach toward the solution of OCPs in the context of complex applications.


Book Synopsis Optimal Control of Partial Differential Equations by : Andrea Manzoni

Download or read book Optimal Control of Partial Differential Equations written by Andrea Manzoni and published by Springer Nature. This book was released on 2022-01-01 with total page 507 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a book on optimal control problems (OCPs) for partial differential equations (PDEs) that evolved from a series of courses taught by the authors in the last few years at Politecnico di Milano, both at the undergraduate and graduate levels. The book covers the whole range spanning from the setup and the rigorous theoretical analysis of OCPs, the derivation of the system of optimality conditions, the proposition of suitable numerical methods, their formulation, their analysis, including their application to a broad set of problems of practical relevance. The first introductory chapter addresses a handful of representative OCPs and presents an overview of the associated mathematical issues. The rest of the book is organized into three parts: part I provides preliminary concepts of OCPs for algebraic and dynamical systems; part II addresses OCPs involving linear PDEs (mostly elliptic and parabolic type) and quadratic cost functions; part III deals with more general classes of OCPs that stand behind the advanced applications mentioned above. Starting from simple problems that allow a “hands-on” treatment, the reader is progressively led to a general framework suitable to face a broader class of problems. Moreover, the inclusion of many pseudocodes allows the reader to easily implement the algorithms illustrated throughout the text. The three parts of the book are suitable to readers with variable mathematical backgrounds, from advanced undergraduate to Ph.D. levels and beyond. We believe that applied mathematicians, computational scientists, and engineers may find this book useful for a constructive approach toward the solution of OCPs in the context of complex applications.


Deterministic and Stochastic Optimal Control and Inverse Problems

Deterministic and Stochastic Optimal Control and Inverse Problems

Author: Baasansuren Jadamba

Publisher: CRC Press

Published: 2021-12-15

Total Pages: 394

ISBN-13: 1000511723

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Inverse problems of identifying parameters and initial/boundary conditions in deterministic and stochastic partial differential equations constitute a vibrant and emerging research area that has found numerous applications. A related problem of paramount importance is the optimal control problem for stochastic differential equations. This edited volume comprises invited contributions from world-renowned researchers in the subject of control and inverse problems. There are several contributions on optimal control and inverse problems covering different aspects of the theory, numerical methods, and applications. Besides a unified presentation of the most recent and relevant developments, this volume also presents some survey articles to make the material self-contained. To maintain the highest level of scientific quality, all manuscripts have been thoroughly reviewed.


Book Synopsis Deterministic and Stochastic Optimal Control and Inverse Problems by : Baasansuren Jadamba

Download or read book Deterministic and Stochastic Optimal Control and Inverse Problems written by Baasansuren Jadamba and published by CRC Press. This book was released on 2021-12-15 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inverse problems of identifying parameters and initial/boundary conditions in deterministic and stochastic partial differential equations constitute a vibrant and emerging research area that has found numerous applications. A related problem of paramount importance is the optimal control problem for stochastic differential equations. This edited volume comprises invited contributions from world-renowned researchers in the subject of control and inverse problems. There are several contributions on optimal control and inverse problems covering different aspects of the theory, numerical methods, and applications. Besides a unified presentation of the most recent and relevant developments, this volume also presents some survey articles to make the material self-contained. To maintain the highest level of scientific quality, all manuscripts have been thoroughly reviewed.


Numerical Methods for Random Parameter Optimal Control and the Optimal Control of Stochastic Differential Equations

Numerical Methods for Random Parameter Optimal Control and the Optimal Control of Stochastic Differential Equations

Author: Tony Huschto

Publisher:

Published: 2014

Total Pages: 198

ISBN-13:

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Book Synopsis Numerical Methods for Random Parameter Optimal Control and the Optimal Control of Stochastic Differential Equations by : Tony Huschto

Download or read book Numerical Methods for Random Parameter Optimal Control and the Optimal Control of Stochastic Differential Equations written by Tony Huschto and published by . This book was released on 2014 with total page 198 pages. Available in PDF, EPUB and Kindle. Book excerpt:


Stochastic Analysis, Control, Optimization and Applications

Stochastic Analysis, Control, Optimization and Applications

Author: William M. McEneaney

Publisher: Springer Science & Business Media

Published: 1999

Total Pages: 892

ISBN-13: 9780817640781

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In view of Professor Wendell Fleming's many fundamental contributions, his profound influence on the mathematical and systems theory communi ties, his service to the profession, and his dedication to mathematics, we have invited a number of leading experts in the fields of control, optimiza tion, and stochastic systems to contribute to this volume in his honor on the occasion of his 70th birthday. These papers focus on various aspects of stochastic analysis, control theory and optimization, and applications. They include authoritative expositions and surveys as well as research papers on recent and important issues. The papers are grouped according to the following four major themes: (1) large deviations, risk sensitive and Hoc control, (2) partial differential equations and viscosity solutions, (3) stochastic control, filtering and parameter esti mation, and (4) mathematical finance and other applications. We express our deep gratitude to all of the authors for their invaluable contributions, and to the referees for their careful and timely reviews. We thank Harold Kushner for having graciously agreed to undertake the task of writing the foreword. Particular thanks go to H. Thomas Banks for his help, advice and suggestions during the entire preparation process, as well as for the generous support of the Center for Research in Scientific Computation. The assistance from the Birkhauser professional staff is also greatly appreciated.


Book Synopsis Stochastic Analysis, Control, Optimization and Applications by : William M. McEneaney

Download or read book Stochastic Analysis, Control, Optimization and Applications written by William M. McEneaney and published by Springer Science & Business Media. This book was released on 1999 with total page 892 pages. Available in PDF, EPUB and Kindle. Book excerpt: In view of Professor Wendell Fleming's many fundamental contributions, his profound influence on the mathematical and systems theory communi ties, his service to the profession, and his dedication to mathematics, we have invited a number of leading experts in the fields of control, optimiza tion, and stochastic systems to contribute to this volume in his honor on the occasion of his 70th birthday. These papers focus on various aspects of stochastic analysis, control theory and optimization, and applications. They include authoritative expositions and surveys as well as research papers on recent and important issues. The papers are grouped according to the following four major themes: (1) large deviations, risk sensitive and Hoc control, (2) partial differential equations and viscosity solutions, (3) stochastic control, filtering and parameter esti mation, and (4) mathematical finance and other applications. We express our deep gratitude to all of the authors for their invaluable contributions, and to the referees for their careful and timely reviews. We thank Harold Kushner for having graciously agreed to undertake the task of writing the foreword. Particular thanks go to H. Thomas Banks for his help, advice and suggestions during the entire preparation process, as well as for the generous support of the Center for Research in Scientific Computation. The assistance from the Birkhauser professional staff is also greatly appreciated.