Probability And Partial Differential Equations In Modern Applied Mathematics

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Author: Edward C. Waymire
Publisher: Springer Science & Business Media
ISBN: 038729371X
Size: 21.88 MB
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Probability And Partial Differential Equations In Modern Applied Mathematics by Edward C. Waymire

Original Title: Probability And Partial Differential Equations In Modern Applied Mathematics

"Probability and Partial Differential Equations in Modern Applied Mathematics" is devoted to the role of probabilistic methods in modern applied mathematics from the perspectives of both a tool for analysis and as a tool in modeling. There is a recognition in the applied mathematics research community that stochastic methods are playing an increasingly prominent role in the formulation and analysis of diverse problems of contemporary interest in the sciences and engineering. A probabilistic representation of solutions to partial differential equations that arise as deterministic models allows one to exploit the power of stochastic calculus and probabilistic limit theory in the analysis of deterministic problems, as well as to offer new perspectives on the phenomena for modeling purposes. There is also a growing appreciation of the role for the inclusion of stochastic effects in the modeling of complex systems. This has led to interesting new mathematical problems at the interface of probability, dynamical systems, numerical analysis, and partial differential equations. This volume will be useful to researchers and graduate students interested in probabilistic methods, dynamical systems approaches and numerical analysis for mathematical modeling in the sciences and engineering.

Functional Analysis In Modern Applied Mathematics

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Publisher: Academic Press
ISBN: 9780080956411
Size: 16.34 MB
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Functional Analysis In Modern Applied Mathematics by

Original Title: Functional Analysis In Modern Applied Mathematics

In this book, we study theoretical and practical aspects of computing methods for mathematical modelling of nonlinear systems. A number of computing techniques are considered, such as methods of operator approximation with any given accuracy; operator interpolation techniques including a non-Lagrange interpolation; methods of system representation subject to constraints associated with concepts of causality, memory and stationarity; methods of system representation with an accuracy that is the best within a given class of models; methods of covariance matrix estimation; methods for low-rank matrix approximations; hybrid methods based on a combination of iterative procedures and best operator approximation; and methods for information compression and filtering under condition that a filter model should satisfy restrictions associated with causality and different types of memory. As a result, the book represents a blend of new methods in general computational analysis, and specific, but also generic, techniques for study of systems theory ant its particular branches, such as optimal filtering and information compression. - Best operator approximation, - Non-Lagrange interpolation, - Generic Karhunen-Loeve transform - Generalised low-rank matrix approximation - Optimal data compression - Optimal nonlinear filtering

Modern Applied Mathematics

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Author: J. C. Misra
Publisher: Alpha Science Int'l Ltd.
ISBN: 9788173194924
Size: 28.13 MB
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Modern Applied Mathematics by J. C. Misra

Original Title: Modern Applied Mathematics

Introduces educational units dealing with important topics of Modern Applied Mathematics. In this book, chapters include information on different topics such as: Methods of Approximation for Mapping in Probability Spaces, Mathematical Modelling of Seismic Sources, Climate Variability, Geometry of Differential Equations, and more.

Introduction To Dynamic Programming

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Author: Leon Cooper
Publisher: Elsevier
ISBN: 1483136620
Size: 34.91 MB
Format: PDF, Mobi
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Introduction To Dynamic Programming by Leon Cooper

Original Title: Introduction To Dynamic Programming

Introduction to Dynamic Programming introduces the reader to dynamic programming and presents the underlying mathematical ideas and results, as well as the application of these ideas to various problem areas. A large number of solved practical problems and computational examples are included to clarify the way dynamic programming is used to solve problems. A consistent notation is applied throughout the text for the expression of quantities such as state variables and decision variables. This monograph consists of 10 chapters and opens with an overview of dynamic programming as a particular approach to optimization, along with the basic components of any mathematical optimization model. The following chapters discuss the application of dynamic programming to variational problems; functional equations and the principle of optimality; reduction of state dimensionality and approximations; and stochastic processes and the calculus of variations. The final chapter looks at several actual applications of dynamic programming to practical problems, such as animal feedlot optimization and optimal scheduling of excess cash investment. This book should be suitable for self-study or for use as a text in a one-semester course on dynamic programming at the senior or first-year, graduate level for students of mathematics, statistics, operations research, economics, business, industrial engineering, or other engineering fields.

Advances In Applied Mathematics Modeling And Computational Science

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Author: Roderick Melnik
Publisher: Springer Science & Business Media
ISBN: 1461453895
Size: 66.18 MB
Format: PDF, Docs
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Advances In Applied Mathematics Modeling And Computational Science by Roderick Melnik

Original Title: Advances In Applied Mathematics Modeling And Computational Science

The volume presents a selection of in-depth studies and state-of-the-art surveys of several challenging topics that are at the forefront of modern applied mathematics, mathematical modeling, and computational science. These three areas represent the foundation upon which the methodology of mathematical modeling and computational experiment is built as a ubiquitous tool in all areas of mathematical applications. This book covers both fundamental and applied research, ranging from studies of elliptic curves over finite fields with their applications to cryptography, to dynamic blocking problems, to random matrix theory with its innovative applications. The book provides the reader with state-of-the-art achievements in the development and application of new theories at the interface of applied mathematics, modeling, and computational science. This book aims at fostering interdisciplinary collaborations required to meet the modern challenges of applied mathematics, modeling, and computational science. At the same time, the contributions combine rigorous mathematical and computational procedures and examples from applications ranging from engineering to life sciences, providing a rich ground for graduate student projects.

Mathematical Aspects Of Scheduling And Applications

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Author: R. Bellman
Publisher: Elsevier
ISBN: 1483137449
Size: 44.98 MB
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Mathematical Aspects Of Scheduling And Applications by R. Bellman

Original Title: Mathematical Aspects Of Scheduling And Applications

Mathematical Aspects of Scheduling and Applications addresses the perennial problem of optimal utilization of finite resources in the accomplishment of an assortment of tasks or objectives. The book provides ways to uncover the core of these problems, presents them in mathematical terms, and devises mathematical solutions for them. The book consists of 12 chapters. Chapter 1 deals with network problems, the shortest path problem, and applications to control theory. Chapter 2 stresses the role and use of computers based on the decision-making problems outlined in the preceding chapter. Chapter 3 classifies scheduling problems and their solution approaches. Chapters 4 to 6 discuss machine sequencing problems and techniques. Chapter 5 tackles capacity expansion problems and introduces the technique of embedded state space dynamic programming for reducing dimensionality so that larger problems can be solved. Chapter 6 then examines an important class of network problems with non-serial phase structures and exploits dimensionality reduction techniques, such as the pseudo-stage concept, branch compression, and optimal order elimination methods to solve large-scale, nonlinear network scheduling problems. Chapters 7 to 11 consider the flow-shop scheduling problem under different objectives and constraints. Chapter 12 discusses the job-shop-scheduling problem. The book will be useful to economists, planners, and graduate students in the fields of mathematics, operations research, management science, computer science, and engineering.

Computational Linguistics

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Author: Nick Cercone
Publisher: Elsevier
ISBN: 1483190617
Size: 44.57 MB
Format: PDF, Kindle
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Computational Linguistics by Nick Cercone

Original Title: Computational Linguistics

Computational Linguistics provides an overview of the variety of important research in computational linguistics in North America. This work is divided into 15 chapters and begins with a survey of the theoretical foundations and parsing strategies for natural language. The succeeding chapters deal with psychological and linguistic modeling, discourse processing analysis, text and content analysis, and natural language understanding, as well as knowledge organization, memory models, and learning. Other chapters describe the programming systems and considerations for computation linguistics. The last chapters look into the nature of natural language front-end processes to database systems. These chapters also examine the human factors interface. This book will prove useful to computing scientists, philosophers, psychologists, and linguists.

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