**Author**: Sebastian Reich,Colin Cotter

**Publisher:**Cambridge University Press

**ISBN:**1107069394

**Category:**Computers

**Page:**306

**View:**5376

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# Search Results for: probabilistic-forecasting-and-bayesian-data-assimilation-cambridge-texts-in-applied-mathematics

**Author**: Sebastian Reich,Colin Cotter

**Publisher:** Cambridge University Press

**ISBN:** 1107069394

**Category:** Computers

**Page:** 306

**View:** 5376

Covers key ideas and concepts. Ideal introduction for graduate students in any field where Bayesian data assimilation is applied.
*The Ensemble Kalman Filter*

**Author**: Geir Evensen

**Publisher:** Springer Science & Business Media

**ISBN:** 3642037119

**Category:** Science

**Page:** 307

**View:** 330

This book reviews popular data-assimilation methods, such as weak and strong constraint variational methods, ensemble filters and smoothers. The author shows how different methods can be derived from a common theoretical basis, as well as how they differ or are related to each other, and which properties characterize them, using several examples. Readers will appreciate the included introductory material and detailed derivations in the text, and a supplemental web site.
*Making Sense of Observations*

**Author**: William Lahoz,Boris Khattatov,Richard Menard

**Publisher:** Springer Science & Business Media

**ISBN:** 9783540747031

**Category:** Science

**Page:** 718

**View:** 3245

Data assimilation methods were largely developed for operational weather forecasting, but in recent years have been applied to an increasing range of earth science disciplines. This book will set out the theoretical basis of data assimilation with contributions by top international experts in the field. Various aspects of data assimilation are discussed including: theory; observations; models; numerical weather prediction; evaluation of observations and models; assessment of future satellite missions; application to components of the Earth System. References are made to recent developments in data assimilation theory (e.g. Ensemble Kalman filter), and to novel applications of the data assimilation method (e.g. ionosphere, Mars data assimilation).
*Ten Lectures on Subjective Computing*

**Author**: Daniela Calvetti,E. Somersalo

**Publisher:** Springer Science & Business Media

**ISBN:** 0387733949

**Category:** Computers

**Page:** 202

**View:** 626

This book has been written for undergraduate and graduate students in various disciplines of mathematics. The authors, internationally recognized experts in their field, have developed a superior teaching and learning tool that makes it easy to grasp new concepts and apply them in practice. The book’s highly accessible approach makes it particularly ideal if you want to become acquainted with the Bayesian approach to computational science, but do not need to be fully immersed in detailed statistical analysis.

**Author**: Mark Asch,Marc Bocquet,Maelle Nodet

**Publisher:** SIAM

**ISBN:** 1611974542

**Category:** Mathematics

**Page:** 306

**View:** 3156

Data assimilation is an approach that combines observations and model output, with the objective of improving the latter. This book places data assimilation into the broader context of inverse problems and the theory, methods, and algorithms that are used for their solution. It provides a framework for, and insight into, the inverse problem nature of data assimilation, emphasizing ?why? and not just ?how.? Methods and diagnostics are emphasized, enabling readers to readily apply them to their own field of study. Readers will find a comprehensive guide that is accessible to nonexperts; numerous examples and diverse applications from a broad range of domains, including geophysics and geophysical flows, environmental acoustics, medical imaging, mechanical and biomedical engineering, economics and finance, and traffic control and urban planning; and the latest methods for advanced data assimilation, combining variational and statistical approaches.
*A Mathematical Introduction*

**Author**: Kody Law,Andrew Stuart,Konstantinos Zygalakis

**Publisher:** Springer

**ISBN:** 3319203258

**Category:** Mathematics

**Page:** 242

**View:** 7044

This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters. This book is aimed at mathematical researchers interested in a systematic development of this interdisciplinary field, and at researchers from the geosciences, and a variety of other scientific fields, who use tools from data assimilation to combine data with time-dependent models. The numerous examples and illustrations make understanding of the theoretical underpinnings of data assimilation accessible. Furthermore, the examples, exercises and MATLAB software, make the book suitable for students in applied mathematics, either through a lecture course, or through self-study.

**Author**: Søren Eilers,Rune Johansen

**Publisher:** Cambridge University Press

**ISBN:** 1107156130

**Category:** Computers

**Page:** 320

**View:** 1804

Mathematics is not, and never will be, an empirical science, but mathematicians are finding that the use of computers and specialized software allows the generation of mathematical insight in the form of conjectures and examples, which pave the way for theorems and their proofs. In this way, the experimental approach to pure mathematics is revolutionizing the way research mathematicians work. As the first of its kind, this book provides material for a one-semester course in experimental mathematics that will give students the tools and training needed to systematically investigate and develop mathematical theory using computer programs written in Maple. Accessible to readers without prior programming experience, and using examples of concrete mathematical problems to illustrate a wide range of techniques, the book gives a thorough introduction to the field of experimental mathematics, which will prepare students for the challenge posed by open mathematical problems.

**Author**: Eugenia Kalnay

**Publisher:** Cambridge University Press

**ISBN:** 9780521796293

**Category:** Mathematics

**Page:** 341

**View:** 7226

This book, first published in 2002, is a graduate-level text on numerical weather prediction, including atmospheric modeling, data assimilation and predictability.

**Author**: Simo Särkkä

**Publisher:** Cambridge University Press

**ISBN:** 110703065X

**Category:** Computers

**Page:** 254

**View:** 1289

A unified Bayesian treatment of the state-of-the-art filtering, smoothing, and parameter estimation algorithms for non-linear state space models.

**Author**: Jinqiao Duan

**Publisher:** Cambridge University Press

**ISBN:** 1107075394

**Category:** Mathematics

**Page:** 307

**View:** 9426

An accessible introduction for applied mathematicians to concepts and techniques for describing, quantifying, and understanding dynamics under uncertainty.

**Author**: Benedict Leimkuhler,Sebastian Reich

**Publisher:** Cambridge University Press

**ISBN:** 9780521772907

**Category:** Mathematics

**Page:** 379

**View:** 6847

Geometric integrators are time-stepping methods, designed such that they exactly satisfy conservation laws, symmetries or symplectic properties of a system of differential equations. In this book the authors outline the principles of geometric integration and demonstrate how they can be applied to provide efficient numerical methods for simulating conservative models. Beginning from basic principles and continuing with discussions regarding the advantageous properties of such schemes, the book introduces methods for the N-body problem, systems with holonomic constraints, and rigid bodies. More advanced topics treated include high-order and variable stepsize methods, schemes for treating problems involving multiple time-scales, and applications to molecular dynamics and partial differential equations. The emphasis is on providing a unified theoretical framework as well as a practical guide for users. The inclusion of examples, background material and exercises enhance the usefulness of the book for self-instruction or as a text for a graduate course on the subject.

**Author**: Hans von Storch,Francis W. Zwiers

**Publisher:** Cambridge University Press

**ISBN:** 1139425099

**Category:** Science

**Page:** N.A

**View:** 5273

Climatology is, to a large degree, the study of the statistics of our climate. The powerful tools of mathematical statistics therefore find wide application in climatological research. The purpose of this book is to help the climatologist understand the basic precepts of the statistician's art and to provide some of the background needed to apply statistical methodology correctly and usefully. The book is self contained: introductory material, standard advanced techniques, and the specialised techniques used specifically by climatologists are all contained within this one source. There are a wealth of real-world examples drawn from the climate literature to demonstrate the need, power and pitfalls of statistical analysis in climate research. Suitable for graduate courses on statistics for climatic, atmospheric and oceanic science, this book will also be valuable as a reference source for researchers in climatology, meteorology, atmospheric science, and oceanography.

**Author**: Andrea Prosperetti,Grétar Tryggvason

**Publisher:** Cambridge University Press

**ISBN:** 1139459902

**Category:** Mathematics

**Page:** N.A

**View:** 1007

Thanks to high-speed computers and advanced algorithms, the important field of modelling multiphase flows is an area of rapid growth. This one-stop account – now in paperback, with corrections from the first printing – is the ideal way to get to grips with this topic, which has significant applications in industry and nature. Each chapter is written by an acknowledged expert and includes extensive references to current research. All of the chapters are essentially independent and so the book can be used for a range of advanced courses and the self-study of specific topics. No other book covers so many topics related to multiphase flow, and it will therefore be warmly welcomed by researchers and graduate students of the subject across engineering, physics, and applied mathematics.

**Author**: Ian Hacking

**Publisher:** Cambridge University Press

**ISBN:** 9780521388849

**Category:** History

**Page:** 264

**View:** 6422

This book combines detailed scientific historical research with characteristic philosophic breadth and verve.
*A Mathematical Introduction*

**Author**: Kody Law,Andrew Stuart,Konstantinos Zygalakis

**Publisher:** Springer

**ISBN:** 3319203258

**Category:** Mathematics

**Page:** 242

**View:** 5564

This book provides a systematic treatment of the mathematical underpinnings of work in data assimilation, covering both theoretical and computational approaches. Specifically the authors develop a unified mathematical framework in which a Bayesian formulation of the problem provides the bedrock for the derivation, development and analysis of algorithms; the many examples used in the text, together with the algorithms which are introduced and discussed, are all illustrated by the MATLAB software detailed in the book and made freely available online. The book is organized into nine chapters: the first contains a brief introduction to the mathematical tools around which the material is organized; the next four are concerned with discrete time dynamical systems and discrete time data; the last four are concerned with continuous time dynamical systems and continuous time data and are organized analogously to the corresponding discrete time chapters. This book is aimed at mathematical researchers interested in a systematic development of this interdisciplinary field, and at researchers from the geosciences, and a variety of other scientific fields, who use tools from data assimilation to combine data with time-dependent models. The numerous examples and illustrations make understanding of the theoretical underpinnings of data assimilation accessible. Furthermore, the examples, exercises and MATLAB software, make the book suitable for students in applied mathematics, either through a lecture course, or through self-study.

**Author**: Andrew F. Bennett

**Publisher:** Cambridge University Press

**ISBN:** 9781139434539

**Category:** Science

**Page:** N.A

**View:** 7696

Inverse Modeling of the Ocean and Atmosphere is a graduate-level book for students of oceanography and meteorology, and anyone interested in combining computer models and observations of the hydrosphere or solid earth. A step-by-step development of maximally efficient inversion algorithms, using ideal models, is complemented by computer codes and comprehensive details for realistic models. Variational tools and statistical concepts are concisely introduced, and applications to contemporary research models, together with elaborate observing systems, are examined in detail. The book offers a review of the various alternative approaches, and further advanced research topics are discussed. Derived from the author's lecture notes, this book constitutes an ideal course companion for graduate students, as well as being a valuable reference source for researchers and managers in theoretical earth science, civil engineering and applied mathematics.

**Author**: Nils J. Nilsson

**Publisher:** Cambridge University Press

**ISBN:** 1139642820

**Category:** Computers

**Page:** N.A

**View:** 9230

Artificial intelligence (AI) is a field within computer science that is attempting to build enhanced intelligence into computer systems. This book traces the history of the subject, from the early dreams of eighteenth-century (and earlier) pioneers to the more successful work of today's AI engineers. AI is becoming more and more a part of everyone's life. The technology is already embedded in face-recognizing cameras, speech-recognition software, Internet search engines, and health-care robots, among other applications. The book's many diagrams and easy-to-understand descriptions of AI programs will help the casual reader gain an understanding of how these and other AI systems actually work. Its thorough (but unobtrusive) end-of-chapter notes containing citations to important source materials will be of great use to AI scholars and researchers. This book promises to be the definitive history of a field that has captivated the imaginations of scientists, philosophers, and writers for centuries.

**Author**: Andrew J. Majda,John Harlim

**Publisher:** Cambridge University Press

**ISBN:** 1107016665

**Category:** Mathematics

**Page:** 357

**View:** 4558

The authors develop a systematic applied mathematics perspective on the problems associated with filtering complex turbulent systems. The book contains background material from filtering, turbulence theory and numerical analysis, making it suitable for graduate courses as well as for researchers in a range of disciplines where applied mathematics is required.

**Author**: Francis Clarke

**Publisher:** Springer Science & Business Media

**ISBN:** 1447148207

**Category:** Mathematics

**Page:** 591

**View:** 7412

Functional analysis owes much of its early impetus to problems that arise in the calculus of variations. In turn, the methods developed there have been applied to optimal control, an area that also requires new tools, such as nonsmooth analysis. This self-contained textbook gives a complete course on all these topics. It is written by a leading specialist who is also a noted expositor. This book provides a thorough introduction to functional analysis and includes many novel elements as well as the standard topics. A short course on nonsmooth analysis and geometry completes the first half of the book whilst the second half concerns the calculus of variations and optimal control. The author provides a comprehensive course on these subjects, from their inception through to the present. A notable feature is the inclusion of recent, unifying developments on regularity, multiplier rules, and the Pontryagin maximum principle, which appear here for the first time in a textbook. Other major themes include existence and Hamilton-Jacobi methods. The many substantial examples, and the more than three hundred exercises, treat such topics as viscosity solutions, nonsmooth Lagrangians, the logarithmic Sobolev inequality, periodic trajectories, and systems theory. They also touch lightly upon several fields of application: mechanics, economics, resources, finance, control engineering. Functional Analysis, Calculus of Variations and Optimal Control is intended to support several different courses at the first-year or second-year graduate level, on functional analysis, on the calculus of variations and optimal control, or on some combination. For this reason, it has been organized with customization in mind. The text also has considerable value as a reference. Besides its advanced results in the calculus of variations and optimal control, its polished presentation of certain other topics (for example convex analysis, measurable selections, metric regularity, and nonsmooth analysis) will be appreciated by researchers in these and related fields.

**Author**: SEON KI PARK,Liang Xu

**Publisher:** Springer Science & Business Media

**ISBN:** 3540710566

**Category:** Science

**Page:** 476

**View:** 7042

Data assimilation (DA) has been recognized as one of the core techniques for modern forecasting in various earth science disciplines including meteorology, oceanography, and hydrology. Since early 1990s DA has been an important s- sion topic in many academic meetings organized by leading societies such as the American Meteorological Society, American Geophysical Union, European G- physical Union, World Meteorological Organization, etc. nd Recently, the 2 Annual Meeting of the Asia Oceania Geosciences Society (AOGS), held in Singapore in June 2005, conducted a session on DA under the - tle of “Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications.” nd This rst DA session in the 2 AOGS was a great success with more than 30 papers presented and many great ideas exchanged among scientists from the three different disciplines. The scientists who participated in the meeting suggested making the DA session a biennial event. th Two years later, at the 4 AOGS Annual Meeting, Bangkok, Thailand, the DA session was of cially named “Sasaki Symposium on Data Assimilation for At- spheric, Oceanic and Hydrologic Applications,” to honor Prof. Yoshi K. Sasaki of the University of Oklahoma for his life-long contributions to DA in geosciences.

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