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An introduction to relativistic processes and the standard model of electroweak interactions
The first part of the volume is devoted to the description of scattering processes in the context of relativistic quantum field theory. The use of the semi-classical approximation allows us to illustrate the relevant computation techniques in a reasonably small amount of space. Our approach to relativistic processes is original in many respects. The second part contains a detailed description of the construction of the standard model of electroweak interactions, with special attention to the mechanism of particle mass generation. The extension of the standard model to include neutrino masses is also described. We have included a number of detailed computations of cross sections and decay rates of pedagogical and phenomenological relevance.
An Introduction to Meshfree Methods and Their Programming
This book aims to present meshfree methods in a friendly and straightforward manner, so that beginners can very easily understand, comprehend, program, implement, apply and extend these methods. It provides first the fundamentals of numerical analysis that are particularly important to meshfree methods. Typical meshfree methods, such as EFG, RPIM, MLPG, LRPIM, MWS and collocation methods are then introduced systematically detailing the formulation, numerical implementation and programming. Many well-tested computer source codes developed by the authors are attached with useful descriptions. The application of the codes can be readily performed using the examples with input and output files given in table form. These codes consist of most of the basic meshfree techniques, and can be easily extended to other variations of more complex procedures of meshfree methods. Readers can easily practice with the codes provided to effective learn and comprehend the basics of meshfree methods.
An Introduction to Mathematics of Emerging Biomedical Imaging
Biomedical imaging is a fascinating research area to applied mathematicians. Challenging imaging problems arise and they often trigger the investigation of fundamental problems in various branches of mathematics. This is the first book to highlight the most recent mathematical developments in emerging biomedical imaging techniques. The main focus is on emerging multi-physics and multi-scales imaging approaches. For such promising techniques, it provides the basic mathematical concepts and tools for image reconstruction. Further improvements in these exciting imaging techniques require continued research in the mathematical sciences, a field that has contributed greatly to biomedical imaging and will continue to do so.
An Introduction to Mathematical Cryptography
This self-contained introduction to modern cryptography emphasizes the mathematics behind the theory of public key cryptosystems and digital signature schemes. The book focuses on these key topics while developing the mathematical tools needed for the construction and security analysis of diverse cryptosystems. Only basic linear algebra is required of the reader; techniques from algebra, number theory, and probability are introduced and developed as required.
An Introduction to Copulas
Copulas are functions that join multivariate distribution functions to their one-dimensional margins. The study of copulas and their role in statistics is a new but vigorously growing field. In this book the student or practitioner of statistics and probability will find discussions of the fundamental properties of copulas and some of their primary applications. The applications include the study of dependence and measures of association, and the construction of families of bivariate distributions.
An Introduction To Chemoinformatics
This, the first text written specifically for this field, aims to provide an introduction to the major techniques of chemoinformatics. The first part of the book deals with the representation of 2D and 3D molecular structures, the calculation of molecular descriptors and the construction of mathematical models. The second part describes other important topics including molecular similarity and diversity, the analysis of large data sets, virtual screening, and library design. Simple illustrative examples are used throughout to illustrate key concepts, supplemented with case studies from the literature.
Algebraic Multiplicity of Eigenvalues of Linear Operators
This book brings together all the most important known results of research into the theory of algebraic multiplicities, from well-known classics like the Jordan Theorem to recent developments such as the uniqueness theorem and the construction of multiplicity for non-analytic families.
Advances in Meshfree Techniques
In recent years meshless/meshfree methods have gained a considerable attention in engineering and applied mathematics. The variety of problems that are now being addressed by these techniques continues to expand and the quality of the results obtained demonstrates the effectiveness of many of the methods currently available. The book presents a significant sample of the state of the art in the field with methods that have reached a certain level of maturity while also addressing many open issues.The book collects extended original contributions presented at the first ECCOMAS Conference on Meshless Methods held in 2005 in Lisbon. The list of contributors reveals a mix of highly distinguished authors as well as quite young but very active and promising researchers, thus giving the reader an interesting and updated view of different mesh reduction methods and its range of applications. The material presented is appropriate for researchers, engineers, physicists, applied mathematicians and graduate students interested in this active research area.
Advances in Discrete Tomography and its Applications
Advances in Discrete Tomography and Its Applications is a unified presentation of new methods, algorithms, and select applications that are the foundations of multidimensional image reconstruction by discrete tomographic methods. The self-contained chapters, written by leading mathematicians, engineers, and computer scientists, present cutting-edge research and results in the field.Three main areas are covered: foundations, algorithms, and practical applications. Following an introduction that reports the recent literature of the field, the book explores various mathematical and computational problems of discrete tomography including new applications.
Advances in Construction Materials 2007
A compilation of recent research results on building construction materials. The construction industry consumes extreme volumes of material, and the growing demand for quality and safety require continuous improvement of materials and material compositions. A deep understanding of material behavior is essential to enable efficient construction: light-weight or heavily burdened structures ask for the development of innovative composites or new material compositions.
Advances in Automatic Differentiation
Covers advances in automatic differentiation theory and practice. Computer scientists and mathematicians will learn about recent developments in automatic differentiation theory as well as mechanisms for the construction of robust and powerful automatic differentiation tools. Computational scientists and engineers will benefit from the discussion of various applications, which provide insight into effective strategies for using automatic differentiation for inverse problems and design optimization.
Adaptronics and Smart Structures : Basics, Materials, Design, and Applications
Adaptronic structures and systems can adapt automatically to variable operating and environmental conditions through the use of feedback control. But in contrast to conventional control loops, in which each function is fulfilled by a separate component, adaptronics is characterized by multifunctional components that are preferably integrated into the structure or the system. The goal is a lightweight and simple construction for conserving material and energy resources. The authors of this book have taken on the task of displaying the current state of the art in this highly modern and strongly interdisciplinary field. Selected application examples are also presented and current development trends demonstrated.
Adaptive Spatial Filters for Electromagnetic Brain Imaging
Adaptive spatial filters are powerful algorithms for electromagnetic brain imaging that enable high-fidelity reconstruction of neuronal activity. This book describes the technical advances of adaptive spatial filters for electromagnetic brain imaging by integrating and synthesizing available information and describes various factors that affect its performance.
