Maths for Engineers 2021-22 HIGHLIGHTS BASICS AND TRENDS IN SENSITIVITY ANALYSIS
METHODS IN COMPUTATIONAL SCIENCE
Theory and Practice in R Sébastien Da Veiga et al
Oct 2021 395pp 9781611976717 Paperback US$89.00
Oct 2021 293pp 9781611976687 Paperback US$89.00
Computational Science and Engineering, Vol. 23 Provides an overview of global sensitivity analysis methods and algorithms, including their theoretical basis and mathematical properties. Throughout, readers can practice applications using the accompanying R code.
Johan Hoffman
Computational Science and Engineering, Vol. 24 Computational methods are an integral part of most scientific disciplines. This textbook introduces computational science through a set of methods and algorithms with the aim of familiarizing the reader with the field's theoretical foundations and providing the practical skills to use and develop computational methods.
MATHEMATICS OF DATA SCIENCE
APPLIED NUMERICAL LINEAR ALGEBRA William W. Hager
A Computational Approach to Clustering and Classification
Nov 2021 424pp 9781611976854 Paperback US$89.00
Classics in Applied Mathematics, Vol. 87
An introduction to numerical issues that arise in linear algebra and its applications which touches on a wide range of techniques, including direct to iterative methods, orthogonal factorizations, least squares, eigenproblems, and nonlinear equations.
LOCATION ESTIMATION FROM THE GROUND UP Sivan Toledo
2020 200pp 9781611976281 Paperback US$67.00
Fundamentals of Algorithms, Vol. 17
The location of an object can often be determined from indirect measurements using a process called estimation. This book explains the mathematical formulation of locationestimation problems and the statistical properties of these mathematical models.
Daniela Calvetti & Erkki Somersalo Feb 2021 189pp 9781611976366 Paperback US$64.00
Data Science, Vol. 1
Provides a solid mathematical basis for understanding popular data science algorithms for clustering and classification and shows that an in-depth understanding of the mathematics powering these algorithms gives insight into the underlying data. It presents a step-by-step derivation of these algorithms.
MINING IMPERFECT DATA With Examples in R
and Python, Second Edition Ronald K. Pearson
2020 481pp 9781611976267 Paperback US$94.00
Mathematics in Industry, Vol. 4
Focuses on the identification and treatment of data anomalies, including examples that highlight different types of anomalies, their potential consequences if left undetected and untreated, and options for dealing with them.
NUMERICAL LINEAR ALGEBRA WITH JULIA
Eric Darve & Mary Wootters
Oct 2021 277pp 9781611976540 Paperback US$89.00
Provides in-depth coverage of fundamental topics in numerical linear algebra, including how to solve dense and sparse linear systems, compute QR factorizations, compute the eigendecomposition of a matrix, and solve linear systems using iterative methods such as conjugate gradient.
MODERN NONCONVEX NONDIFFERENTIABLE OPTIMIZATION
Ying Cui & Jong-Shi Pang Dec 2021 774pp 9781611976731 Hardback US$119.00
MOS-SIAM Series on Optimization, Vol. 29
Starting with the fundamentals of classical smooth optimization and building on established convex programming techniques, this research monograph provides a foundation and methodology for modern nonconvex nondifferentiable optimization.
NUMERICAL HOMOGENIZATION BY LOCALIZED ORTHOGONAL DECOMPOSITION A. Målqvist & D. Peterseim
2020 108pp 9781611976441 Paperback US$44.00
SIAM Spotlights, Vol. 5
Presents the first survey of the Localized Orthogonal Decomposition (LOD) method, a pioneering approach for the numerical homogenization of partial differential equations with multiscale data beyond periodicity and scale separation.
OBSERVABILITY
A New Theory Based on the Group of Invariance Agostino Martinelli 2020 262pp 9781611976243 Paperback US$84.00
Advances in Design and Control, Vol. 37
Explores nonlinear observability. The book provides a modern theory of observability based on a new paradigm borrowed from theoretical physics and the mathematical foundation of that paradigm.
PETSc FOR PARTIAL DIFFERENTIAL EQUATIONS
If you are a teaching academic or course leader you may request up to three titles as FREE inspection copies to consider as textbooks for students on your course. For further details please visit: eurospan.co.uk/inspection
Numerical Solutions in C and Python Ed Bueler Jan 2021 391pp 9781611976304 Paperback US$94.00
Software, Environments, and Tools, Vol. 31
The Portable, Extensible Toolkit for Scientific Computation (PETSc) is an open-source library of advanced data structures and methods for solving linear and nonlinear equations and for managing discretizations. This book uses these modern numerical tools to demonstrate how to solve nonlinear partial differential equations in parallel.
BESTSELLERS
Recent Advances and Applications Alain Miranville 2019 216pp 9781611975918 Paperback US$69.00
CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 95
Presents a detailed discussion of both classical and recent results on the popular Cahn-Hilliard equation and some of its variants.
COMPUTING HIGHLY OSCILLATORY INTEGRALS Alfredo Deaño, Daan Huybrechs & Arieh Iserles 2018 182pp 9781611975116 Paperback US$81.50
Highly oscillatory phenomena range across numerous areas in science and engineering and their computation represents a difficult challenge. This is the only monograph bringing together the new body of ideas in this area in its entirety.
DIFFERENTIAL DYNAMICAL SYSTEMS
DYNAMIC MODE DECOMPOSITION
GAUSSIAN MEASURES
J. Nathan Kutz et al
2015 433pp 9781470418694 Paperback US$116.00
Data-Driven Modeling of Complex Systems
2016 250pp 9781611974492 Paperback US$74.00
The first book to address the DMD algorithm presenting a pedagogical and comprehensive approach to all aspects of DMD currently developed or under development.
Gives a systematic exposition of the modern theory of Gaussian measures. This work presents fundamental facts about finite and infinite dimensional Gaussian distributions.
MATRIX ANALYSIS FOR SCIENTISTS & ENGINEERS
Uri M. Ascher & Chen Greif
Alan J. Laub
2011 574pp 9780898719970 Paperback US$108.00
2004 170pp 9780898715767 Paperback US$54.50
Computational Science & Engineering, Vol. 7
Avoiding encyclopaedic and heavily theoretical exposition, this book provides an in-depth treatment of fundamental issues and methods, the reasons behind the success and failure of numerical software, and fresh and easy-to-follow approaches and techniques.
GAME THEORY WITH ENGINEERING APPLICATIONS Dario Bauso
Revised Second Edition
James D. Meiss
Advances in Design and Control, Vol. 30
2017 420pp 9781611974638 Paperback US$90.00
Addresses the foundations of game theory, with an emphasis on the physical intuition behind the concepts, an analysis of design techniques, and a discussion of new trends in the study of cooperation and competition in large complex distributed systems.
Combines much of the material found in a traditional course on ordinary differential equations with an introduction to the more modern theory of dynamical systems.
Mathematical Surveys and Monographs, Vol. 62
A FIRST COURSE IN NUMERICAL METHODS
2016 312pp 9781611974270 Paperback US$88.00
Mathematical Modeling and Computation, Vol. 22
Vladimir I. Bogachev
Provides a blend of undergraduate- and graduate-level topics in matrix theory and linear algebra that relieves instructors of the burden of reviewing such material in subsequent courses that depend heavily on the language of matrices.
UNCERTAINTY QUANTIFICATION Theory, Implementation, and Applications Ralph C. Smith 2013 400pp 9781611973211 Hardback US$81.50
Computational Science & Engineering, Vol. 12
Provides readers with the basic concepts, theory, and algorithms necessary to quantify input and response uncertainties for simulation models arising in a broad range of disciplines.
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SIATBJ1021
THE CAHN–HILLIARD EQUATION