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An Introduction to Computational Stochastic PDEs
This book offers a practical presentation of stochastic partial differential equations arising in physical applications and their numerical approximation.
Introduction to Magnetohydrodynamics
Comprehensive textbook prioritising physical ideas over mathematical detail. New material includes fusion plasma magnetohydrodynamics.
An Introduction to Polynomial and Semi-Algebraic Optimization
The first comprehensive introduction to the powerful moment approach for solving global optimization problems.
Microhydrodynamics, Brownian Motion, and Complex Fluids
Provides a foundation for understanding complex fluids by integrating fluid dynamics, statistical physics, and polymer and colloid science.
Stochastic Methods in Neuroscience
Great interest is now being shown in computational and mathematical neuroscience, fuelled in part by the rise in computing power, the ability to record large amounts of neurophysiological data, and advances in stochastic analysis. These techniques are leading to biophysically more realistic models. It has also become clear that both neuroscientists and mathematicians profit from collaborations in this exciting research area.Graduates and researchers in computational neuroscience and stochastic systems, and neuroscientists seeking to learn more about recent advances in the modelling and analysis of noisy neural systems, will benefit from this comprehensive overview. The series of self-contain...
Numerical Linear Algebra
This self-contained introduction to numerical linear algebra provides a comprehensive, yet concise, overview of the subject. It includes standard material such as direct methods for solving linear systems and least-squares problems, error, stability and conditioning, basic iterative methods and the calculation of eigenvalues. Later chapters cover more advanced material, such as Krylov subspace methods, multigrid methods, domain decomposition methods, multipole expansions, hierarchical matrices and compressed sensing. The book provides rigorous mathematical proofs throughout, and gives algorithms in general-purpose language-independent form. Requiring only a solid knowledge in linear algebra and basic analysis, this book will be useful for applied mathematicians, engineers, computer scientists, and all those interested in efficiently solving linear problems.
Geometric and Topological Inference
A rigorous introduction to geometric and topological inference, for anyone interested in a geometric approach to data science.
Discrete Systems and Integrability
A first introduction to the theory of discrete integrable systems at a level suitable for students and non-experts.
Stochastic Modelling of Reaction-Diffusion Processes
Practical introduction for advanced undergraduate or beginning graduate students of applied mathematics, developed at the University of Oxford.
Pattern Formation in Continuous and Coupled Systems
This IMA Volume in Mathematics and its Applications PATTERN FORMATION IN CONTINUOUS AND COUPLED SYSTEMS is based on the proceedings of a workshop with the same title, but goes be yond the proceedings by presenting a series of mini-review articles that sur vey, and provide an introduction to, interesting problems in the field. The workshop was an integral part of the 1997-98 IMA program on "EMERG ING APPLICATIONS OF DYNAMICAL SYSTEMS." I would like to thank Martin Golubitsky, University of Houston (Math ematics) Dan Luss, University of Houston (Chemical Engineering), and Steven H. Strogatz, Cornell University (Theoretical and Applied Mechan ics) for their excellent work as organizers of the m...
