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Numerical continuation methods have provided important contributions toward the numerical solution of nonlinear systems of equations for many years. This book, originally published in 1979, was the first book to provide easy access to the numerical aspects of predictor corrector continuation and piecewise linear continuation methods.
A very broad coverage of the most applicable aspects of stochastic processes.
This book was the first and remains the only book to give a comprehensive treatment of the behaviour of linear or nonlinear systems when they are connected in a closed-loop fashion, with the output of one system forming the input of the other.
In order to emphasize the relationships and cohesion between analytical and numerical techniques, this book presents a comprehensive and integrated treatment of both aspects in combination with the modelling of relevant problem classes.
Provides a comprehensive, tutorial-style introduction to the algorithms for reconstructing cross-sectional images from projection data and contains a complete overview of the engineering and signal processing algorithms necessary for tomographic imaging.
No one working in duality should be without a copy of this book. It contains different developments of infinite dimensional convex programming in the context of convex analysis, including duality, minmax and Lagrangians, and convexification of nonconvex optimization problems in the calculus of variations (infinite dimension).
Presents the mathematical knowledge needed in order to understand the art of computing eigenvalues of real symmetric matrices,
A survey of mathematical models useful in solving reliability problems.
Readers will find this book an invaluable reference on the design of experiments. It contains hard-to-find information on topics such as change-over designs with residual effects and early treatment of analysis of covariance.
Offers an alternative to the "rote" approach of presenting standard categories of differential equations accompanied by routine problem sets. The exercises presented amplify and provide perspective for the material, often giving readers opportunity for ingenuity.
This book addresses the construction, analysis, and intepretation of mathematical models that reveal significant problems in the physical sciences.
Develops a general theory of nonsmooth analysis and geometry together with a set of associated techniques.
This book has become the standard for a complete, state-of-the-art description of the methods for unconstrained optimization and systems of nonlinear equations. Originally published in 1983, it provides information needed to understand both the theory and the practice of these methods and provides pseudocode for the problems.
Provides a rigorous mathematical analysis of the behavior of nonlinear control systems under a variety of situations. This book develops nonlinear generalizations of a large number of techniques and methods widely used in linear control theory.
Mathematical Models in Biology is an introductory book for readers interested in biological applications of mathematics and modeling in biology.
A research reference for all those interested in operator theory, linear algebra, and numerical analysis.
Focuses on the fundamental ideas of continuum mechanics by analysing models of fluid flow and solid deformation and examining problems in elasticity, water waves, and extremum principles. It provides an overview of the subject, with an emphasis on clarity, explanation, and motivation.
Offers a rare blend of linear algebra, convex analysis, and statistics. Since the book's initial publication in 1993, readers have used its methods to derive optimal designs on the circle, optimal mixture designs, and optimal designs in other statistical models.
Originally published in 1988, this book deals with identification (in the sense of obtaining a model from data) of multi-input and multi-output linear systems, in particular systems in ARMAX and state space form.
A reprint of the original volume, which won the Lanchester Prize awarded by the Operations Research Society of America for the best work of 1968. Although out of print for nearly 15 years, it remains one of the most referenced volumes in the field of mathematical programming.
This revised edition discusses numerical methods for computing eigenvalues and eigenvectors of large sparse matrices. It provides an in-depth view of the numerical methods that are applicable for solving matrix eigenvalue problems that arise in various engineering and scientific applications.
A concise, rigorous, yet accessible, account of the fundamentals of constrained optimization theory.
This mathematically rigorous book remains the standard reference on the linear complementarity problem. Its comprehensive treatment of the computation of equilibria arising from engineering, economics, and finance, plus chapter-ending exercises and "Notes and References" sections make it equally useful for a graduate-level course or for self-study.
An accessible text for the study of numerical methods for solving least squares problems remains an essential part of a scientific software foundation. Numerical analysts, statisticians, and engineers have developed techniques and nomenclature for the least squares problems of their own discipline.
Introduces the general theory of order statistics and their applications. The book covers topics such as distribution theory for order statistics from continuous and discrete populations, moment relations, bounds and approximations, order statistics in statistical inference and characterization results, and basic asymptotic theory
This SIAM Classics edition of the 1986 book provides the theoretical foundation for representative control applications.
Covers the fundamentals of the theory of ordinary differential equations.
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