Bernd Hofmann

Thomas Schuster

Barbara Kaltenbacher

Kamil S. Kazimierski

Regularization methods aimed at finding stable approximate solutions are a necessary tool to tackle inverse and ill-posed problems. Usually the mathematical model of an inverse problem consists of an operator equation of the first kind and often the associated forward operator acts between Hilbert spaces. However, for numerous problems the reasons for using a Hilbert space setting seem to be based rather on conventions than on an approprimate and realistic model choice, so often a Banach space setting would be closer to reality. Furthermore, sparsity constraints using general Lp-norms or the BV-norm have recently become very popular. Meanwhile the most well-known methods have been investigated for linear and nonlinear operator equations in Banach spaces. Motivated by these facts the authors aim at collecting and publishing these results in a monograph.

Regularization Methods in Banach Spaces

Anne Wald

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.

Time-dependent Problems in Imaging and Parameter Identification

Rolf Lammering

Ulrich Gabbert

Michael Sinapius

Peter Wierach

The book focuses especially on the application of SHM technology to thin walled structural systems made from carbon fiber reinforced plastics. Here, guided elastic waves (Lamb-waves) show an excellent sensitivity to structural damages so that they are in the center of this book. It is divided into 4 sections dealing with analytical, numerical and experimental fundamentals, and subsequently with Lamb-wave propagation in fiber reinforced composites, SHM-systems and signal processing. The book is designed for engineering students as well as for researchers in the field of structural health monitoring and for users of this technology.

Lamb-Wave Based Structural Health Monitoring in Polymer Composites

In recent years there has been a great influx of sources for business and financial news, yet the hope that this financial media boom would lead to the democratization of the financial markets has not been realized. Thomas Schuster's The Markets and the Media explores why the expansion of economic communication has proven to be of only limited benefit, arguing that the financial media boom has had negative repercussions resulting in substantial costs for the individual as well as the system. The Markets and the Media stands alone in its class: It is the first comprehensive analysis focusing on the complex, intricate, and often puzzling relationship between the financial markets and the mass media. Featuring a comprehensive business bibliography, this book is a must-read for both finance experts and media scholars.

Thomas Schuster

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