Karsten Urban – författare

This textbook introduces the study of partial differential equations using both analytical and numerical methods. By intertwining the two complementary approaches, the authors create an ideal foundation for further study. Motivating examples from the physical sciences, engineering, and economics complete this integrated approach.

A showcase of models begins the book, demonstrating how PDEs arise in practical problems that involve heat, vibration, fluid flow, and financial markets. Several important characterizing properties are used to classify mathematical similarities, then elementary methods are used to solve examples of hyperbolic, elliptic, and parabolic equations. From here, an accessible introduction to Hilbert spaces and the spectral theorem lay the foundation for advanced methods. Sobolev spaces are presented first in dimension one, before being extended to arbitrary dimension for the study of elliptic equations. An extensive chapter on numerical methods focuses onfinite difference and finite element methods. Computer-aided calculation with Maple™ completes the book. Throughout, three fundamental examples are studied with different tools: Poisson’s equation, the heat equation, and the wave equation on Euclidean domains. The Black–Scholes equation from mathematical finance is one of several opportunities for extension.

Partial Differential Equations offers an innovative introduction for students new to the area. Analytical and numerical tools combine with modeling to form a versatile toolbox for further study in pure or applied mathematics. Illuminating illustrations and engaging exercises accompany the text throughout. Courses in real analysis and linear algebra at the upper-undergraduate level are assumed.

Consisting of  four contributions presented at the CIME summer school, the book presents several points of view and techniques to solve demanding problems of increasing complexity. The focus is on theoretical investigation and applicative algorithm development for reduction in the complexity – the dimension, the degrees of freedom, the data – arising in these models.

The special volume offers a global guide to new concepts and approaches concerning the following topics: reduced basis methods, proper orthogonal decomposition, proper generalized decomposition, approximation theory related to model reduction, learning theory and compressed sensing, stochastic and high-dimensional problems, system-theoretic methods, nonlinear model reduction, reduction of coupled problems/multiphysics, optimization and optimal control, state estimation and control, reduced order models and domain decomposition methods, Krylov-subspace and interpolatory methods, and applications to real industrial and complex problems.

The book represents the state of the art in the development of reduced order methods. It contains contributions from internationally respected experts, guaranteeing a wide range of expertise and topics. Further, it reflects an important effor

Though not a textbook, some of the chapters can be used as reference materials or lecture notes for classes and tutorials (doctoral schools, master classes).

Dieses Lehrbuch gibt eine Einführung in die partiellen Differenzialgleichungen. Wir beginnen mit einigen ganz konkreten Beispielen aus den Natur-, Ingenieur und Wirtschaftswissenschaften. Danach werden elementare Lösungsmethoden dargestellt, z.B. für die Black-Scholes-Gleichung aus der Finanzmathematik. Schließlich wird die analytische Untersuchung großer Klassen von partiellen Differenzialgleichungen dargestellt, wobei Hilbert-Raum-Methoden im Mittelpunkt stehen.

Numerische Verfahren werden eingeführt und mit konkreten Beispielen behandelt.

Zu jedem Kapitel finden sich Übungsaufgaben, mit deren Hilfe der Stoff eingeübt und vertieft werden kann.

Dieses Buch richtet sich an Studierende im Bachelor oder im ersten Master-Jahr sowohl in der (Wirtschafts-)Mathematik als auch in den Studiengängen Informatik, Physik und Ingenieurwissenschaften.

Stimme zur ersten Auflage

Auf dieses Lehrbuch haben wir gewartet.

Prof. Dr. Andreas Kleinert in zbMATH