- Table View
- List View
Geometric Modeling and Mesh Generation from Scanned Images (Chapman & Hall/CRC Mathematical and Computational Imaging Sciences Series #6)
by Yongjie Jessica ZhangCutting-Edge Techniques to Better Analyze and Predict Complex Physical Phenomena Geometric Modeling and Mesh Generation from Scanned Images shows how to integrate image processing, geometric modeling, and mesh generation with the finite element method (FEM) to solve problems in computational biology, medicine, materials science, and engineering. Based on the author’s recent research and course at Carnegie Mellon University, the text explains the fundamentals of medical imaging, image processing, computational geometry, mesh generation, visualization, and finite element analysis. It also explores novel and advanced applications in computational biology, medicine, materials science, and other engineering areas. One of the first to cover this emerging interdisciplinary field, the book addresses biomedical/material imaging, image processing, geometric modeling and visualization, FEM, and biomedical and engineering applications. It introduces image-mesh-simulation pipelines, reviews numerical methods used in various modules of the pipelines, and discusses several scanning techniques, including ones to probe polycrystalline materials. The book next presents the fundamentals of geometric modeling and computer graphics, geometric objects and transformations, and curves and surfaces as well as two isocontouring methods: marching cubes and dual contouring. It then describes various triangular/tetrahedral and quadrilateral/hexahedral mesh generation techniques. The book also discusses volumetric T-spline modeling for isogeometric analysis (IGA) and introduces some new developments of FEM in recent years with applications.
International Conference on Biomedical and Health Informatics: Icbhi2015, Haikou, China, 8-10 October 2015 (IFMBE Proceedings #64)
by Yuan-Ting Zhang Paulo Carvalho Ratko Magjarevic<P><P>This volume presents the proceedings of the International Conference on Biomedical and Health Informatics (ICBHI). The conference was a new special topic conference and a common initiative by the International Federation of Medical and Biological Engineering (IFMBE) and IEEE Engineering in Medicine and Biology Society (IEEE- EMBS). BHI2015 was held in Haikou, China, 8-10 October 2015. The main theme of the BHI2015 is “The Convergence: Integrating Information and Communication Technologies with Biomedicine for Global Health”. <P><P> The ICBHI2015 proceedings examine enabling technologies of sensors, devices and systems that optimize the acquisition, transmission, processing, storage, retrieval, use of biomedical and health information as well as to report novel clinical applications of health information systems and the deployment of m-Health, e-Health, u-Health, p-Health and Telemedicine.
Repetitive Motion Planning and Control of Redundant Robot Manipulators
by Yunong Zhang Zhijun ZhangRepetitive Motion Planning and Control of Redundant Robot Manipulators presents four typical motion planning schemes based on optimization techniques, including the fundamental RMP scheme and its extensions. These schemes are unified as quadratic programs (QPs), which are solved by neural networks or numerical algorithms. The RMP schemes are demonstrated effectively by the simulation results based on various robotic models; the experiments applying the fundamental RMP scheme to a physical robot manipulator are also presented. As the schemes and the corresponding solvers presented in the book have solved the non-repetitive motion problems existing in redundant robot manipulators, it is of particular use in applying theoretical research based on the quadratic program for redundant robot manipulators in industrial situations. This book will be a valuable reference work for engineers, researchers, advanced undergraduate and graduate students in robotics fields. Yunong Zhang is a professor at The School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China; Zhijun Zhang is a research fellow working at the same institute.
Frame Theory in Data Science (Advances in Science, Technology & Innovation)
by Zhihua Zhang Palle E. JorgensenThis book establishes brand-new frame theory and technical implementation in data science, with a special focus on spatial-scale feature extraction, network dynamics, object-oriented analysis, data-driven environmental prediction, and climate diagnosis. Given that data science is unanimously recognized as a core driver for achieving Sustainable Development Goals of the United Nations, these frame techniques bring fundamental changes to multi-channel data mining systems and support the development of digital Earth platforms. This book integrates the authors' frame research in the past twenty years and provides cutting-edge techniques and depth for scientists, professionals, and graduate students in data science, applied mathematics, environmental science, and geoscience.
Variational, Topological, and Partial Order Methods with Their Applications
by Zhitao ZhangNonlinear functional analysis is an important branch of contemporary mathematics. It's related to topology, ordinary differential equations, partial differential equations, groups, dynamical systems, differential geometry, measure theory, and more. In this book, the author presents some new and interesting results on fundamental methods in nonlinear functional analysis, namely variational, topological and partial order methods, which have been used extensively to solve existence of solutions for elliptic equations, wave equations, Schrödinger equations, Hamiltonian systems etc., and are also used to study the existence of multiple solutions and properties of solutions. This book is useful for researchers and graduate students in the field of nonlinear functional analysis.
Statistical Implications of Turing's Formula
by Zhiyi ZhangFeatures a broad introduction to recent research on Turing's formula and presents modern applications in statistics, probability, information theory, and other areas of modern data science Turing's formula is, perhaps, the only known method for estimating the underlying distributional characteristics beyond the range of observed data without making any parametric or semiparametric assumptions. This book presents a clear introduction to Turing's formula and its connections to statistics. Topics with relevance to a variety of different fields of study are included such as information theory; statistics; probability; computer science inclusive of artificial intelligence and machine learning; big data; biology; ecology; and genetics. The author provides examinations of many core statistical issues within modern data science from Turing's perspective. A systematic approach to long-standing problems such as entropy and mutual information estimation, diversity index estimation, domains of attraction on general alphabets, and tail probability estimation is presented in light of the most up-to-date understanding of Turing's formula. Featuring numerous exercises and examples throughout, the author provides a summary of the known properties of Turing's formula and explains how and when it works well; discusses the approach derived from Turing's formula in order to estimate a variety of quantities, all of which mainly come from information theory, but are also important for machine learning and for ecological applications; and uses Turing's formula to estimate certain heavy-tailed distributions. In summary, this book: * Features a unified and broad presentation of Turing's formula, including its connections to statistics, probability, information theory, and other areas of modern data science * Provides a presentation on the statistical estimation of information theoretic quantities * Demonstrates the estimation problems of several statistical functions from Turing's perspective such as Simpson's indices, Shannon's entropy, general diversity indices, mutual information, and Kullback-Leibler divergence * Includes numerous exercises and examples throughout with a fundamental perspective on the key results of Turing's formula Statistical Implications of Turing's Formula is an ideal reference for researchers and practitioners who need a review of the many critical statistical issues of modern data science. This book is also an appropriate learning resource for biologists, ecologists, and geneticists who are involved with the concept of diversity and its estimation and can be used as a textbook for graduate courses in mathematics, probability, statistics, computer science, artificial intelligence, machine learning, big data, and information theory. Zhiyi Zhang, PhD, is Professor of Mathematics and Statistics at The University of North Carolina at Charlotte. He is an active consultant in both industry and government on a wide range of statistical issues, and his current research interests include Turing's formula and its statistical implications; probability and statistics on countable alphabets; nonparametric estimation of entropy and mutual information; tail probability and biodiversity indices; and applications involving extracting statistical information from low-frequency data space. He earned his PhD in Statistics from Rutgers University.
Numerical Methods for Stochastic Partial Differential Equations with White Noise
by Zhongqiang Zhang George Em KarniadakisThis book covers numerical methods for stochastic partial differential equations with white noise using the framework of Wong-Zakai approximation. The book begins with some motivational and background material in the introductory chapters and is divided into three parts. Part I covers numerical stochastic ordinary differential equations. Here the authors start with numerical methods for SDEs with delay using the Wong-Zakai approximation and finite difference in time. Part II covers temporal white noise. Here the authors consider SPDEs as PDEs driven by white noise, where discretization of white noise (Brownian motion) leads to PDEs with smooth noise, which can then be treated by numerical methods for PDEs. In this part, recursive algorithms based on Wiener chaos expansion and stochastic collocation methods are presented for linear stochastic advection-diffusion-reaction equations. In addition, stochastic Euler equations are exploited as an application of stochastic collocation methods, where a numerical comparison with other integration methods in random space is made. Part III covers spatial white noise. Here the authors discuss numerical methods for nonlinear elliptic equations as well as other equations with additive noise. Numerical methods for SPDEs with multiplicative noise are also discussed using the Wiener chaos expansion method. In addition, some SPDEs driven by non-Gaussian white noise are discussed and some model reduction methods (based on Wick-Malliavin calculus) are presented for generalized polynomial chaos expansion methods. Powerful techniques are provided for solving stochastic partial differential equations. This book can be considered as self-contained. Necessary background knowledge is presented in the appendices. Basic knowledge of probability theory and stochastic calculus is presented in Appendix A. In Appendix B some semi-analytical methods for SPDEs are presented. In Appendix C an introduction to Gauss quadrature is provided. In Appendix D, all the conclusions which are needed for proofs are presented, and in Appendix E a method to compute the convergence rate empirically is included. In addition, the authors provide a thorough review of the topics, both theoretical and computational exercises in the book with practical discussion of the effectiveness of the methods. Supporting Matlab files are made available to help illustrate some of the concepts further. Bibliographic notes are included at the end of each chapter. This book serves as a reference for graduate students and researchers in the mathematical sciences who would like to understand state-of-the-art numerical methods for stochastic partial differential equations with white noise.
Complex-Valued Neural Networks Systems with Time Delay: Stability Analysis and (Anti-)Synchronization Control (Intelligent Control and Learning Systems #4)
by Ziye Zhang Zhen Wang Jian Chen Chong LinThis book provides up-to-date developments in the stability analysis and (anti-)synchronization control area for complex-valued neural networks systems with time delay. It brings out the characteristic systematism in them and points out further insight to solve relevant problems. It presents a comprehensive, up-to-date, and detailed treatment of dynamical behaviors including stability analysis and (anti-)synchronization control. The materials included in the book are mainly based on the recent research work carried on by the authors in this domain.The book is a useful reference for all those from senior undergraduates, graduate students, to senior researchers interested in or working with control theory, applied mathematics, system analysis and integration, automation, nonlinear science, computer and other related fields, especially those relevant scientific and technical workers in the research of complex-valued neural network systems, dynamic systems, and intelligent control theory.
Chinese Students' Higher Achievement in Mathematics: Comparison of Mathematics Education of Australian and Chinese Primary Schools (Mathematics Education – An Asian Perspective #0)
by Dacheng ZhaoThis book shares insights into the achievement gap in mathematics between East Asian and Western countries, and the ways to improve students' mathematics achievements. Especially, it highlights the importance to integrate case studies with large-scale international comparative studies in general, and comparative studies of mathematics education in particular. This book is a must-read for mathematics teachers, mathematics educators, educational researchers, education administrators, curriculum developers, assessment designers, and student teachers who are interested in mathematics education and how to improve students' mathematics achievements.
Computer Vision Using Local Binary Patterns: Computer Vision Using Local Binary Patterns (Computational Imaging and Vision #40)
by Guoying Zhao Matti Pietikäinen Timo Ahonen Abdenour HadidThe recent emergence of Local Binary Patterns (LBP) has led to significant progress in applying texture methods to various computer vision problems and applications. The focus of this research has broadened from 2D textures to 3D textures and spatiotemporal (dynamic) textures. Also, where texture was once utilized for applications such as remote sensing, industrial inspection and biomedical image analysis, the introduction of LBP-based approaches have provided outstanding results in problems relating to face and activity analysis, with future scope for face and facial expression recognition, biometrics, visual surveillance and video analysis. Computer Vision Using Local Binary Patterns provides a detailed description of the LBP methods and their variants both in spatial and spatiotemporal domains. This comprehensive reference also provides an excellent overview as to how texture methods can be utilized for solving different kinds of computer vision and image analysis problems. Source codes of the basic LBP algorithms, demonstrations, some databases and a comprehensive LBP bibliography can be found from an accompanying web site. Topics include: local binary patterns and their variants in spatial and spatiotemporal domains, texture classification and segmentation, description of interest regions, applications in image retrieval and 3D recognition - Recognition and segmentation of dynamic textures, background subtraction, recognition of actions, face analysis using still images and image sequences, visual speech recognition and LBP in various applications. Written by pioneers of LBP, this book is an essential resource for researchers, professional engineers and graduate students in computer vision, image analysis and pattern recognition. The book will also be of interest to all those who work with specific applications of machine vision.
Knowledge Graph and Semantic Computing. Knowledge Computing and Language Understanding: Third China Conference, CCKS 2018, Tianjin, China, August 14–17, 2018, Revised Selected Papers (Communications in Computer and Information Science #957)
by Jun Zhao Frank Van Harmelen Jie Tang Xianpei Han Quan Wang Xianyong LiThis book constitutes the refereed proceedings of the Third China Conference on Knowledge Graph and Semantic Computing, CCKS 2018, held in Tianjin, China, in August 2018.The 27 revised full papers and 2 revised short papers presented were carefully reviewed and selected from 101 submissions. The papers cover wide research fields including the knowledge graph, information extraction, knowledge representation and reasoning, linked data.
Supply Chain Finance: Integrating Operations and Finance in Global Supply Chains (Euro Advanced Tutorials On Operational Research)
by Lima Zhao Arnd HuchzermeierThis textbook presents a coherent and robust structure for integrated risk management in the context of operations and finance. It explains how the operations-finance interface jointly optimizes material and financial flows under intricate risk exposures. The book covers financial flexibility, operational hedging, enterprise risk management (ERM), supply chain risk management (SCRM), integrated risk management (IRM), supply chain finance (SCF), and financial management of supply chain strategies. Both qualitative and quantitative approaches – including conceptualization, theory building, analytical modeling, and empirical research – are used to assess the value creation by integrating operations and finance. “This book provides a comprehensive description of the interactions between finance and operations and of how managers can best make decisions in recognition of these effects.” John R. Birge, University of Chicago“Supply chain finance is an emerging area where innovations can unlock great values to complement the advances in information and physical flows of supply chain.” Hau L. Lee, Stanford University“This book provides an excellent overview of supply chain finance and its most recent advances.” Jan A. Van Mieghem, Northwestern University“This book is indispensable for advanced students as well as practitioners when looking for a pedagogical sound and scientific rigorous approach to Supply Chain Finance.” Ralf W. Seifert, IMD/EPFL“The book advances our knowledge on the interface between operations and finance and provides managerial guidelines for effective risk management in the supply chain.” Xiande Zhao, CEIBS
Population Aging and Age-Friendly Transport in China (Population, Regional Development and Transport)
by Pengjun Zhao Jinxin XieThis book is the first book that investigates aging and its impacts on transport system in China. Using various data, this book covers, but is not limited to, the development of population aging, the changes of travel demand, the features of travel behavior of China’s elderly, progress and prospect of age-friendly transport in China. The book has international academic novelty in three points. Firstly, it discovers the long-term supply-demand relationship between population aging and transport infrastructure development. Secondly, it finds the changes and factors in travel behavior of the elderly people. Thirdly, it discusses the advantages or disadvantages of age-friendly transport policy. The findings in the book provide fresh evidences for the challenges posed by aging to transport and enhance readers’ existing knowledge of the elderly people’s travel behavior and the related determinants. These findings are helpful for planners and politicians to make age-friendly transport policies and useful for investors and enterprises to supply proper transport services to the elderly people. This book is of great interest to scholars and practitioners interested in transport development, transport policy, social transition, sustainable mobility, urban planning, urban governance and is relevant to China and other developing countries.
The Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach (Chapman & Hall/CRC Monographs on Statistics and Applied Probability #1)
by Shanshan Zhao Ross PrenticeThe Statistical Analysis of Multivariate Failure Time Data: A Marginal Modeling Approach provides an innovative look at methods for the analysis of correlated failure times. The focus is on the use of marginal single and marginal double failure hazard rate estimators for the extraction of regression information. For example, in a context of randomized trial or cohort studies, the results go beyond that obtained by analyzing each failure time outcome in a univariate fashion. The book is addressed to researchers, practitioners, and graduate students, and can be used as a reference or as a graduate course text. Much of the literature on the analysis of censored correlated failure time data uses frailty or copula models to allow for residual dependencies among failure times, given covariates. In contrast, this book provides a detailed account of recently developed methods for the simultaneous estimation of marginal single and dual outcome hazard rate regression parameters, with emphasis on multiplicative (Cox) models. Illustrations are provided of the utility of these methods using Women’s Health Initiative randomized controlled trial data of menopausal hormones and of a low-fat dietary pattern intervention. As byproducts, these methods provide flexible semiparametric estimators of pairwise bivariate survivor functions at specified covariate histories, as well as semiparametric estimators of cross ratio and concordance functions given covariates. The presentation also describes how these innovative methods may extend to handle issues of dependent censorship, missing and mismeasured covariates, and joint modeling of failure times and covariates, setting the stage for additional theoretical and applied developments. This book extends and continues the style of the classic Statistical Analysis of Failure Time Data by Kalbfleisch and Prentice. Ross L. Prentice is Professor of Biostatistics at the Fred Hutchinson Cancer Research Center and University of Washington in Seattle, Washington. He is the recipient of COPSS Presidents and Fisher awards, the AACR Epidemiology/Prevention and Team Science awards, and is a member of the National Academy of Medicine. Shanshan Zhao is a Principal Investigator at the National Institute of Environmental Health Sciences in Research Triangle Park, North Carolina.
Data Intensive Industrial Asset Management: IoT-based Algorithms and Implementation
by Tian Zhao Farhad Balali Jessie Nouri Adel NasiriThis book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors provide a comprehensive study which includes the descriptive, diagnostic, predictive, and prescriptive analysis in detail. The presentation focuses on the challenges of the parameter selection, statistical data analysis, predictive algorithms, big data storage and selection, data pattern recognition, machine learning techniques, asset failure distribution estimation, reliability and availability enhancement, condition based maintenance policy, failure detection, data driven optimization algorithm, and a multi-objective optimization approach, all of which can significantly enhance the reliability and availability of the system.
Information Modeling for Interoperable Dimensional Metrology
by Y Zhao Robert Brown T Kramer Xun XuDimensional metrology is an essential part of modern manufacturing technologies, but the basic theories and measurement methods are no longer sufficient for today's digitized systems. The information exchange between the software components of a dimensional metrology system not only costs a great deal of money, but also causes the entire system to lose data integrity. Information Modeling for Interoperable Dimensional Metrology analyzes interoperability issues in dimensional metrology systems and describes information modeling techniques. It discusses new approaches and data models for solving interoperability problems, as well as introducing process activities, existing and emerging data models, and the key technologies of dimensional metrology systems. Written for researchers in industry and academia, as well as advanced undergraduate and postgraduate students, this book gives both an overview and an in-depth understanding of complete dimensional metrology systems. By covering in detail the theory and main content, techniques, and methods used in dimensional metrology systems, Information Modeling for Interoperable Dimensional Metrology enables readers to solve real-world dimensional measurement problems in modern dimensional metrology practices.
Modern Statistical Methods for Health Research (Emerging Topics in Statistics and Biostatistics)
by Yichuan Zhao Din Ding-Geng ChenThis book brings together the voices of leading experts in the frontiers of biostatistics, biomedicine, and the health sciences to discuss the statistical procedures, useful methods, and novel applications in biostatistics research. It also includes discussions of potential future directions of biomedicine and new statistical developments for health research, with the intent of stimulating research and fostering the interactions of scholars across health research related disciplines. Topics covered include: Health data analysis and applications to EHR data Clinical trials, FDR, and applications in health science Big network analytics and its applications in GWAS Survival analysis and functional data analysis Graphical modelling in genomic studies The book will be valuable to data scientists and statisticians who are working in biomedicine and health, other practitioners in the health sciences, and graduate students and researchers in biostatistics and health.
New Frontiers of Biostatistics and Bioinformatics (ICSA Book Series in Statistics)
by Yichuan Zhao Ding-Geng ChenThis book is comprised of presentations delivered at the 5th Workshop on Biostatistics and Bioinformatics held in Atlanta on May 5-7, 2017. Featuring twenty-two selected papers from the workshop, this book showcases the most current advances in the field, presenting new methods, theories, and case applications at the frontiers of biostatistics, bioinformatics, and interdisciplinary areas.Biostatistics and bioinformatics have been playing a key role in statistics and other scientific research fields in recent years. The goal of the 5th Workshop on Biostatistics and Bioinformatics was to stimulate research, foster interaction among researchers in field, and offer opportunities for learning and facilitating research collaborations in the era of big data. The resulting volume offers timely insights for researchers, students, and industry practitioners.
Sparse Optimization Theory and Methods
by Yun-Bin ZhaoSeeking sparse solutions of underdetermined linear systems is required in many areas of engineering and science such as signal and image processing. The efficient sparse representation becomes central in various big or high-dimensional data processing, yielding fruitful theoretical and realistic results in these fields. The mathematical optimization plays a fundamentally important role in the development of these results and acts as the mainstream numerical algorithms for the sparsity-seeking problems arising from big-data processing, compressed sensing, statistical learning, computer vision, and so on. This has attracted the interest of many researchers at the interface of engineering, mathematics and computer science. Sparse Optimization Theory and Methods presents the state of the art in theory and algorithms for signal recovery under the sparsity assumption. The up-to-date uniqueness conditions for the sparsest solution of underdertemined linear systems are described. The results for sparse signal recovery under the matrix property called range space property (RSP) are introduced, which is a deep and mild condition for the sparse signal to be recovered by convex optimization methods. This framework is generalized to 1-bit compressed sensing, leading to a novel sign recovery theory in this area. Two efficient sparsity-seeking algorithms, reweighted l1-minimization in primal space and the algorithm based on complementary slackness property, are presented. The theoretical efficiency of these algorithms is rigorously analysed in this book. Under the RSP assumption, the author also provides a novel and unified stability analysis for several popular optimization methods for sparse signal recovery, including l1-mininization, Dantzig selector and LASSO. This book incorporates recent development and the author’s latest research in the field that have not appeared in other books.
Spectral Feature Selection for Data Mining (Chapman And Hall/crc Data Mining And Knowledge Discovery Ser.)
by Zheng Alan Zhao Huan LiuSpectral Feature Selection for Data Mining introduces a novel feature selection technique that establishes a general platform for studying existing feature selection algorithms and developing new algorithms for emerging problems in real-world applications. This technique represents a unified framework for supervised, unsupervised, and semisupervise
Routledge Handbook of Asian Demography
by Zhongwei Zhao Adrian C. HayesHome to close to 60 per cent of the world’s population, Asia is the largest and by far the most populous continent. It is also extremely diverse, physically and culturally. Asian countries and regions have their own distinctive histories, cultural traditions, religious beliefs and political systems, and they have often pursued different routes to development. Asian populations also present a striking array of demographic characteristics and stages of demographic transition. This handbook is the first to provide a comprehensive study of population change across the whole of Asia. Comprising 28 chapters by more than 40 international experts this handbook examines demographic transitions on the continent, their considerable variations, their causes and consequences, and their relationships with a wide range of social, economic, political and cultural processes. Major topics covered include: population studies and sources of demographic data; historical demography; family planning and fertility decline; sex preferences; mortality changes; causes of death; HIV/AIDS; population distribution and migration; urbanization; marriage and family; human capital and labour force; population ageing; demographic dividends; political demography; population and environment; and Asia’s demographic future. This handbook provides an authoritative and comprehensive reference for researchers, policymakers, academics, students and anyone who is interested in population change in Asia and the world.
Large-Scale Perturbations of Magnetohydrodynamic Regimes
by Vladislav ZheligovskyNew developments for hydrodynamical dynamo theory have been spurred by recent evidence of self-sustained dynamo activity in laboratory experiments with liquid metals. The emphasis in the present volume is on the introduction of powerful mathematical techniques required to tackle modern multiscale analysis of continous systems and there application to a number of realistic model geometries of increasing complexity. This introductory and self-contained research monograph summarizes the theoretical state-of-the-art to which the author has made pioneering contributions.
Theory of Spinors and Its Application in Physics and Mechanics
by Vladimir A. ZhelnorovichThis book contains a systematic exposition of the theory of spinors in finite-dimensional Euclidean and Riemannian spaces. The applications of spinors in field theory and relativistic mechanics of continuous media are considered. The main mathematical part is connected with the study of invariant algebraic and geometric relations between spinors and tensors. The theory of spinors and the methods of the tensor representation of spinors and spinor equations are thoroughly expounded in four-dimensional and three-dimensional spaces. Very useful and important relations are derived that express the derivatives of the spinor fields in terms of the derivatives of various tensor fields.The problems associated with an invariant description of spinors as objects that do not depend on the choice of a coordinate system are addressed in detail. As an application, the author considers an invariant tensor formulation of certain classes of differential spinor equations containing, in particular, the most important spinor equations of field theory and quantum mechanics. Exact solutions of the Einstein–Dirac equations, nonlinear Heisenberg’s spinor equations, and equations for relativistic spin fluids are given. The book presents a large body of factual material and is suited for use as a handbook. It is intended for specialists in theoretical physics, as well as for students and post-graduate students of physical and mathematical specialties.
Spline and Spline Wavelet Methods with Applications to Signal and Image Processing
by Valery A. Zheludev Pekka Neittaanmäki Amir Z. AverbuchThis book presents various contributions of splines to signal and image processing from a unified perspective that is based on the Zak transform (ZT). It expands the methodology from periodic splines, which were presented in the first volume, to non-periodic splines. Together, these books provide a universal toolbox accompanied by MATLAB software for manipulating polynomial and discrete splines, spline-based wavelets, wavelet packets and wavelet frames for signal/ image processing applications. In this volume, we see that the ZT provides an integral representation of discrete and polynomial splines, which, to some extent, is similar to Fourier integral. The authors explore elements of spline theory and design, and consider different types of polynomial and discrete splines. They describe applications of spline-based wavelets to data compression. These splines are useful for real-time signal processing and, in particular, real-time wavelet and frame transforms. Further topics addressed in this volume include: "global" splines, such as interpolating, self-dual and smoothing, whose supports are infinite; the compactly supported quasi-interpolating and smoothing splines including quasi-interpolating splines on non-uniform grids; and cubic Hermite splines as a source for the design of multiwavelets and multiwavelet frames. Readers from various disciplines including engineering, computer science and mathematical information technology will find the descriptions of algorithms, applications and software in this book especially useful.
Analysis of Genetic Association Studies (Statistics for Biology and Health)
by Gang Zheng Xiaofeng Zhu Yaning Yang Robert C. ElstonAnalysis of Genetic Association Studies is both a graduate level textbook in statistical genetics and genetic epidemiology, and a reference book for the analysis of genetic association studies. Students, researchers, and professionals will find the topics introduced in Analysis of Genetic Association Studies particularly relevant. The book is applicable to the study of statistics, biostatistics, genetics and genetic epidemiology. In addition to providing derivations, the book uses real examples and simulations to illustrate step-by-step applications. Introductory chapters on probability and genetic epidemiology terminology provide the reader with necessary background knowledge. The organization of this work allows for both casual reference and close study.