The goal of this book is to introduce the reader to methodologies in recovery problems for objects, such as functions and signals, from partial or indirect information. The recovery of objects from a set of data demands key solvers of inverse and sampling problems. Until recently, connections between the mathematical areas of inverse problems and sampling were rather tenuous. However, advances in several areas of mathematical research have revealed deep common threads between them, which proves that there is a serious need for a unifying description of the underlying mathematical ideas and concepts. Freeden and Nashed present an integrated approach to resolution methodologies from the perspective of both these areas. Researchers in sampling theory will benefit from learning about inverse problems and regularization methods, while specialists in inverse problems will gain a better understanding of the point of view of sampling concepts. This book requires some basic knowledge of functional analysis, Fourier theory, geometric number theory, constructive approximation, and special function theory. By avoiding extreme technicalities and elaborate proof techniques, it is an accessible resource for students and researchers not only from applied mathematics, but also from all branches of engineering and science.

Iwasawa theory began in the late 1950s with a series of papers by Kenkichi Iwasawa on ideal class groups in the cyclotomic tower of number fields and their relation to $p$-adic $L$-functions. The theory was later generalized by putting it in the context of elliptic curves and modular forms. The main motivation for writing this book was the need for a total perspective of Iwasawa theory that includes the new trends of generalized Iwasawa theory. Another motivation is to update the classical theory for class groups, taking into account the changed point of view on Iwasawa theory. The goal of this second part of the three-part publication is to explain various aspects of the cyclotomic Iwasawa theory of $p$-adic Galois representations.

The book provides the geoscientific context, that arises in gravimetric/magnetometric exploration. It essentially uses mathematics as a key technology for modeling issues on the basis of analysis and interpretation according to dense and precise gravitational/magnetic measurements. It is dedicated to surface and deep geology with potential data primarily of terrestrial origin. The book spans the interdisciplinary arc from geoengineering, especially geodesy, via geophysics to geomathematics and geology, and back again. It presents the recently published pioneering and groundbreaking multiscale mollifier methodologies realizing the bridging transfer from gravitational/magnetic measurements to approximative/numerical mollifier wavelet decorrelations with novel geologic prospects and layer-structure determination as outcome. Using the specific example of the German Saarland region, new important fields of application, especially for areas with mining-related cavities, will be opened up and subjected to an in-depth geologic detection.

A comprehensive review of the advances of smart cities’ smart energy, transportation, infrastructure, and health Smart Energy for Transportation and Health in a Smart City offers an essential guide to the functions, characteristics, and domains of smart cities and the energy technology necessary to sustain them. The authors—noted experts on the topic—include the theoretical underpinnings, the practical information, and the potential benefits for the development of smart cities. The book includes information on various financial models of energy storage, the management of networked micro-grids, coordination of virtual energy storage systems, reliability modeling and assessment of cyber space, and the development of a vehicle-to-grid voltage support. The authors review smart transportation elements such as the advanced metering infrastructure for electric vehicle charging, power system dispatching with plug-in hybrid electric vehicles, and the best practices for low power wide area network technologies. In addition, the book explores smart health that is based on the Internet of Things and smart devices that can help improve patient care processes and decrease costs while maintaining quality. This important resource: Examines the challenges and opportunities that arise with the development of smart cities Presents a state-of-the-art financial models of smart energy storage Clearly explores the elements of a smart city based on the advancement of information and communication technology Contains a review of advances in smart health for smart cities Includes a variety of real-life case studies that illustrate the various components of a smart city Written for practicing engineers and engineering students, Smart Energy for Transportation and Health in Smart Cities offers a practical guide to the various aspects that create a sustainable smart city.

Concepts in Projection-Reconstruction, by Ray Freeman and Ēriks Kupče.- Automated Projection Spectroscopy and Its Applications, by Sebastian Hiller and Gerhard Wider.- Data Sampling in Multidimensional NMR: Fundamentals and Strategies, by Mark W. Maciejewski, Mehdi Mobli, Adam D. Schuyler, Alan S. Stern and Jeffrey C. Hoch.- Generalized Fourier Transform for Non-Uniform Sampled Data, by Krzysztof Kazimierczuk, Maria Misiak, Jan Stanek, Anna Zawadzka-Kazimierczuk and Wiktor Koźmiński.- Applications of Non-Uniform Sampling and Processing, by Sven G. Hyberts, Haribabu Arthanari and Gerhard Wagner

Signal Recovery Techniques for Image and Video Compression and Transmission establishes a bridge between the fields of signal recovery and image and video compression. Traditionally these fields have developed separately because the problems they examined were regarded as very different, and the techniques used appear unrelated. Recently, though, there is growing consent among the research community that the two fields are quite closely related. Indeed, in both fields the objective is to reconstruct the best possible signal from limited information. The field of signal recovery, which is relatively mature, has long been associated with a wealth of powerful mathematical techniques such as Bayesian estimation and the theory of projects onto convex sets (to name just two). This book illustrates for the first time in a complete volume how these techniques can be brought to bear on the very important problems of image and video compression and transmission. Signal Recovery Techniques for Image and Video Compression and Transmission, which is written by leading practitioners in both fields, is one of the first references that addresses this approach and serves as an excellent information source for both researchers and practicing engineers.

This book covers recent advances in image processing and imaging sciences from an optimization viewpoint, especially convex optimization with the goal of designing tractable algorithms. Throughout the handbook, the authors introduce topics on the most key aspects of image acquisition and processing that are based on the formulation and solution of novel optimization problems. The first part includes a review of the mathematical methods and foundations required, and covers topics in image quality optimization and assessment. The second part of the book discusses concepts in image formation and capture from color imaging to radar and multispectral imaging. The third part focuses on sparsity constrained optimization in image processing and vision and includes inverse problems such as image restoration and de-noising, image classification and recognition and learning-based problems pertinent to image understanding. Throughout, convex optimization techniques are shown to be a critically important mathematical tool for imaging science problems and applied extensively. Convex Optimization Methods in Imaging Science is the first book of its kind and will appeal to undergraduate and graduate students, industrial researchers and engineers and those generally interested in computational aspects of modern, real-world imaging and image processing problems.