Eine vollständige Liste aller am Institut für Mathematik verfassten Fachbücher finden Sie in der Forschungsdokumentation (FoDok).
Ausgewählte Fachbücher
Barbara Kaltenbacher, William Rundell: Inverse Problems for Fractional Partial Differential Equations, American Mathematical Society, US Providence (RI), 2023
As the title of the book indicates, this is primarily a book on partial differential equations (PDEs) with two definite slants: toward inverse problems and to the inclusion of fractional derivatives. The standard paradigm, or direct problem, is to take a PDE, including all coefficients and initial/boundary conditions, and to determine the solution. The inverse problem reverses this approach asking what information about coefficients of the model can be obtained from partial information on the solution. Answering this question requires knowledge of the underlying physical model, including the exact dependence on material parameters.
The last feature of the approach taken by the authors is the inclusion of fractional derivatives. This is driven by direct physical applications: a fractional derivative model often allows greater adherence to physical observations than the traditional integer order case.
The book also has an extensive historical section and the material that can be called „fractional calculus“ and ordinary differential equations with fractional derivatives. This part is accessible to advanced undergraduates with basic knowledge on real and complex analysis. At the other end of the spectrum, lie nonlinear fractional PDEs that require a standard graduate level course on PDEs.
Vasso Anagnostopoulou, Christian Pötzsche, Martin Rasmussen: Nonautonomous Bifurcation Theory, Springer, Cham, 2023
Bifurcation theory is a major topic in dynamical systems theory with profound applications. However, in contrast to autonomous dynamical systems, it is not clear what a bifurcation of a nonautonomous dynamical system actually is, and so far, various different approaches to describe qualitative changes have been suggested in the literature. The aim of this book is to provide a concise survey of the area and equip the reader with suitable tools to tackle nonautonomous problems. A review, discussion and comparison of several concepts of bifurcation is provided, and these are formulated in a unified notation and illustrated by means of comprehensible examples. Additionally, certain relevant tools needed in a corresponding analysis are presented.
Barbara Kaltenbacher, Thomas Schuster, Anne Wald: Time-dependent Problems in Imaging and Parameter Identification, Springer, Heidelberg, 2021
Inverse problems such as imaging or parameter identification deal with the recovery of unknown quantities from indirect observations, connected via a model describing the underlying context. While traditionally inverse problems are formulated and investigated in a static setting, we observe a significant increase of interest in time-dependence in a growing number of important applications over the last few years. Here, time-dependence affects a) the unknown function to be recovered and / or b) the observed data and / or c) the underlying process. Challenging applications in the field of imaging and parameter identification are techniques such as photoacoustic tomography, elastography, dynamic computerized or emission tomography, dynamic magnetic resonance imaging, super-resolution in image sequences and videos, health monitoring of elastic structures, optical flow problems or magnetic particle imaging to name only a few. Such problems demand for innovation concerning their mathematical description and analysis as well as computational approaches for their solution.
Gert Kadunz: Zeichen und Sprache im Mathematikunterricht, Springer, Heidelberg, 2020
This volume presents different aspects of teaching and learning mathematics from the perspective of Peirce’s semiotics. The contributions demonstrate the flexibility of this tool from both a practical and theoretical point of view.
The range of topics is diverse: there are texts on the visualization of mathematics at different school levels, on sign language, on gesture research, and on multilingual mathematics teaching. One contribution describes the visible as a means of creativity for constructing new knowledge, while another traces the reconstruction of diagrammatic reasoning. In addition, a perspective on learning mathematics is presented that does not rely on restrictive ontological assumptions.
Barbara Kaltenbacher, Igor Kukavica, Irena Lasiecka, Roberto Triggiani, Amjad Tuffaha, Justin T. Webster: Mathematical Theory of Evolutionary Fluid-Flow Structure Interactions, Springer, Cham, 2018
This book is devoted to the study of coupled partial differential equation models, which describe complex dynamical systems occurring in modern scientific applications such as fluid/flow-structure interactions. The first chapter provides a general description of a fluid-structure interaction, which is formulated within a realistic framework, where the structure subject to a frictional damping moves within the fluid. The second chapter then offers a multifaceted description, with often surprising results, of the case of the static interface; a case that is argued in the literature to be a good model for small, rapid oscillations of the structure. The third chapter describes flow-structure interaction where the compressible Navier-Stokes equations are replaced by the linearized Euler equation, while the solid is taken as a nonlinear plate, which oscillates in the surrounding gas flow. The final chapter focuses on a the equations of nonlinear acoustics coupled with linear acousticsor elasticity, as they arise in the context of high intensity ultrasound applications.
Nicolo Gusmeroli: Machine Scheduling to Minimize Weighted Completion Times, Springer, Heidelberg, 2018
This work reviews the most important results regarding the use of the α-point in Scheduling Theory. It provides a number of different LP-relaxations for scheduling problems and seeks to explain their polyhedral consequences. It also explains the concept of the α-point and how the conversion algorithm works, pointing out the relations to the sum of the weighted completion times. Lastly, the book explores the latest techniques used for many scheduling problems with different constraints, such as release dates, precedences, and parallel machines. This reference book is intended for advanced undergraduate and postgraduate students who are interested in scheduling theory. It is also inspiring for researchers wanting to learn about sophisticated techniques and open problems of the field.
Gert Kadunz, Norma Presmeg, Luis Radford, Michael Roth: Semiotics in Mathematics Education, Springer, Berlin, 2016
This volume discusses semiotics in mathematics education as an activity with a formal sign system, in which each sign represents something else. Theories presented by Saussure, Peirce, Vygotsky and other writers on semiotics are summarized in their relevance to the teaching and learning of mathematics. The significance of signs for mathematics education lies in their ubiquitous use in every branch of mathematics. Such use involves seeing the general in the particular, a process that is not always clear to learners. Therefore, in several traditional frameworks, semiotics has the potential to serve as a powerful conceptual lens in investigating diverse topics in mathematics education research. Topics that are implicated include (but are not limited to): the birth of signs; embodiment, gestures and artifacts; segmentation and communicative fields; cultural mediation; social semiotics; linguistic theories; chains of signification; semiotic bundles; relationships among various sign systems; intersubjectivity; diagrammatic and inferential reasoning; and semiotics as the focus of innovative learning and teaching materials.
Christian Pötzsche, Clemens Heuberger, Barbara Kaltenbacher, Franz Rendl: System Modeling and Optimization, Springer, Heidelberg, 2014
This book is a collection of thoroughly refereed papers presented at the 26th IFIP TC 7 Conference on System Modeling and Optimization, held in Klagenfurt, Austria, in September 2013. The 34 revised papers were carefully selected from numerous submissions. They cover the latest progress in a wide range of topics such as optimal control of ordinary and partial differential equations, modeling and simulation, inverse problems, nonlinear, discrete, and stochastic optimization as well as industrial applications.
Peter Kloeden, Christian Pötzsche: Nonautonomous dynamical systems in the life sciences, Springer, Heidelberg, 2013
Nonautonomous dynamics describes the qualitative behavior of evolutionary differential and difference equations, whose right-hand side is explicitly time dependent. Over recent years, the theory of such systems has developed into a highly active field related to, yet recognizably distinct from that of classical autonomous dynamical systems. This development was motivated by problems of applied mathematics, in particular in the life sciences where genuinely nonautonomous systems abound. The purpose of this monograph is to indicate through selected, representative examples how often nonautonomous systems occur in the life sciences and to outline the new concepts and tools from the theory of nonautonomous dynamical systems that are now available for their investigation.
Thomas Schuster, Barbara Kaltenbacher, Bernd Hofmann, Kamil S. Kazimierski: Regularization Methods in Banach Spaces, de Gruyter, Berlin, 2012
Regularization methods aimed at finding stable approximate solutions are a
necessary tool to tackle inverse and ill-posed problems. Inverse problems arise in
a large variety of applications ranging from medical imaging and nondestructive
testing via finance to systems biology. Many of these problems
belong to the class of parameter identification problems in partial differential
equations (PDEs) and thus are computationally demanding and mathematically
challenging. Hence there is a substantial need for stable and efficient solvers for
this kind of problems as well as for a rigorous convergence analysis of these
methods.
This monograph consists of five parts. Part I motivates the importance of
developing and analyzing regularization methods in Banach spaces by
presenting four applications which intrinsically demand for a Banach space
setting and giving a brief glimpse of sparsity constraints. Part II summarizes all
mathematical tools that are necessary to carry out an analysis in Banach spaces.
Part III represents the current state-of-the-art concerning Tikhonov
regularization in Banach spaces. Part IV about iterative regularization methods is
concerned with linear operator equations and the iterative solution of nonlinear
operator equations by gradient type methods and the iteratively regularized
Gauß-Newton method. Part V finally outlines the method of approximate inverse
which is based on the efficient evaluation of the measured data with
reconstruction kernels.
Christian Pötzsche: Geometric theory of discrete nonautonomous dynamical systems, Springer, Heidelberg, 2010
Nonautonomous dynamical systems provide a mathematical framework for temporally changing phenomena, where the law of evolution varies in time due to seasonal, modulation, controlling or even random effects. Our goal is to provide an approach to the corresponding geometric theory of nonautonomous discrete dynamical systems in infinite-dimensional spaces by virtue of 2-parameter semigroups (processes). These dynamical systems are generated by implicit difference equations, which explicitly depend on time. Compactness and dissipativity conditions are provided for such problems in order to have attractors using the natural concept of pullback convergence. Concerning a necessary linear theory, our hyperbolicity concept is based on exponential dichotomies and splittings. This concept is in turn used to construct nonautonomous invariant manifolds, so-called fiber bundles, and deduce linearization theorems. The results are illustrated using temporal and full discretizations of evolutionary differential equations.
Barbara Kaltenbacher, Andreas Neubauer, Otmar Scherzer: Iterative Regularization Methods for Nonlinear Ill-Posed Problems, De Gruyter, Berlin, 2008
Nonlinear inverse problems appear in many applications, and typically they lead
to mathematical models that are ill-posed, i.e., they are unstable under data
perturbations. Those problems require a regularization, i.e., a special numerical
treatment. This book presents regularization schemes which are based on
iteration methods, e.g., nonlinear Landweber iteration, level set methods,
multilevel methods and Newton type methods.
