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This book collects, explains and analyses basic methods and recent results for the successful numerical solution of singularly perturbed differential equations. Such equations model many physical phenomena and their solutions are characterized by the presence of layers. The book is a wide-ranging introduction to the exciting current literature in this area. It concentrates on linear convection-diffusion equations and related nonlinear flow problems, encompassing both ordinary and partial differential equations. While many numerical methods are considered, particular attention is paid to those with realistic error estimates. The book provides a solid and thorough foundation for the numerical analysis and solution of singular perturbation problems.
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Symmetry is the key to solving differential equations. There are many well-known techniques for obtaining exact solutions, but most of them are special cases of a few powerful symmetry methods. Furthermore, these methods can be applied to differential equations of an unfamiliar type; they do not rely on special 'tricks'. Instead, a given differential equation is forced to reveal its symmetries, which are then used to construct exact solutions. This book is a straightforward introduction to the subject, and is aimed at applied mathematicians, physicists, and engineers. The presentation is informal, using many worked examples to illustrate the main symmetry methods. It is written at a level suitable for postgraduates and advanced undergraduates, and is designed to enable the reader to master the main techniques quickly and easily. The book contains methods that have not previously appeared in a text. These include methods for obtaining discrete symmetries and integrating factors.
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"The treatment of inverse theory in this book is divided into four parts. Chapters 1 and 2 provide a general background, explaining what inverse problems are and what constitutes their solution as well as reviewing some of the basic concepts from linear algebra and probability theory that will be applied throughout the text. Chapters 3-7 discuss the solution of the canonical inverse problem : the linear problem with Gaussian statistics. This is the best understood of all inverse problems; and it is here that the fundamental notions of uncertainty, uniqueness, and resolution can be most clearly developed. Chapters 8-11 extend the discussion to problems that are non-Gaussian, nonlinear and continuous. Chapters 12-13 provide examples of the use of inverse theory and a discussion of the steps that must be taken to solve inverse problems on a computer"-- Provided by publisher
Geophysics - Measurement. --- Geophysics -- Measurement. --- Inverse problems (Differential equations) - Numerical solutions. --- Inverse problems (Differential equations) -- Numerical solutions. --- Oceanography - Measurement. --- Oceanography -- Measurement. --- Geophysics --- Oceanography --- Inverse problems (Differential equations) --- Physics --- Physical Sciences & Mathematics --- Cosmic Physics --- Measurement --- Numerical solutions --- Measurement. --- Numerical solutions. --- Oceanography, Physical --- Oceanology --- Physical oceanography --- Thalassography --- Geological physics --- Terrestrial physics --- Earth sciences --- Marine sciences --- Ocean --- Numerical analysis --- Geophysics - Measurement --- Oceanography - Measurement --- Inverse problems (Differential equations) - Numerical solutions
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