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Stereographic Projection Techniques for Geologists and Civil Engineers
by Richard J. Lisle Peter R. LeyshonThe stereographic projection is an essential tool in the fields of structural geology and geotechnics, which allows three-dimensional orientation data to be represented and manipulated. This book has been designed to make the subject as accessible as possible. It gives a straightforward and simple introduction to the subject and, by means of examples, illustrations and exercises, encourages the student to visualise the problems in three dimensions. Students of all levels will be able to work through the book and come away with a clear understanding of how to apply these vital techniques. This revised edition contains additional material on geotechnical applications, improved illustrations and links to useful web resources and software programs. It will provide students of geology, rock mechanics, geotechnical and civil engineering with an indispensable guide to the analysis and interpretation of field orientation data.
Stereology for Statisticians (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
by Adrian Baddeley Eva B. JensenSetting out the principles of stereology from a statistical viewpoint, this book focuses on both basic theory and practical implications. The authors discuss ways to effectively communicate statistical issues to clients, draw attention to common methodological errors, and provide references to essential literature. The first full text on design-bas
Stereoscopic HDTV
by Hirokazu Yamanoue Masaki Emoto Yuji NojiriThis book focuses on the two psychological factors of naturalness and ease of viewing of three-dimensional high-definition television (3D HDTV) images. It has been said that distortions peculiar to stereoscopic images, such as the "puppet theater" effect or the "cardboard" effect, spoil the sense of presence. Whereas many earlier studies have focused on geometrical calculations about these distortions, this book instead describes the relationship between the naturalness of reproduced 3D HDTV images and the nonlinearity of depthwise reproduction. The ease of viewing of each scene is regarded as one of the causal factors of visual fatigue. Many of the earlier studies have been concerned with the accurate extraction of local parallax; however, this book describes the typical spatiotemporal distribution of parallax in 3D images. The purpose of the book is to examine the correlations between the psychological factors and amount of characteristics of parallax distribution in order to understand the characteristics of easy- and difficult-to-view images and then to seek to create a new 3D HDTV system that minimizes visual fatigue for the viewer. The book is an important resource for researchers who wish to investigate and better understand various psychological effects caused by stereoscopic images.
Stereotomy: Stone Construction and Geometry in Western Europe 1200–1900 (Mathematics and the Built Environment #4)
by José Calvo-LópezThis book deals with the general concepts in stereotomy and its connection with descriptive geometry, the social background of its practitioners and theoreticians, the general methods and tools of this technology, and the specific procedures for the members built in hewn stone, including arches, squinches, stairs and vaults, ending with a chapter discussing the open problems in this field. Thus, it can be used as a reference book in the subject, but it can also read as a compelling narrative on this subject, one of the main branches of pre-industrial technology. Construction in hewn stone requires the use of geometrical methods and tools to assure that individual stones, either blocks or voussoirs, fit with one another and conform to the general shape of walls, arches or vaults. During the Late Middle Ages and the Renaissance, such techniques and instruments were developed empirically by masons and architects. Later on, learned mathematicians and engineers introduced refinements in these procedures and this branch of knowledge, known as stereotomy, furnished much material to descriptive geometry, a science born with the French Revolution which provided the foundation for projective geometry.
Steven Weinberg: A Life in Physics
by Steven WeinbergSteven Weinberg shares his candid thoughts, in his own words, on theoretical physics and cosmology, along with personal anecdotes and recollections of the people who helped shape his career. These memoirs of his life as a scientist and public figure cover his student days and early career, through the golden age of particle physics in the 1970s, his being awarded the Nobel prize, through to the end of the twentieth century. In addition to his research insights, Weinberg provides glimpses into his life in academia more broadly: dealing with the 'two-body problem', tenure, international conference travel, his book-writing, advisory work with JASON, and his advocacy for the Superconducting Super Collider. Physicists, historians of science and interested readers will find the presentation engaging and often witty, as Weinberg reflects on his life in physics.
Stichproben
by Göran Kauermann Helmut KüchenhoffDas Buch führt in Grundprinzipien der Stichprobenziehung und der zugehörigen statistischen Auswertung ein. Dabei stehen Motivation und anschauliche Beschreibung der Verfahren im Vordergrund. Nach einer generellen Einführung werden sowohl modellbasierte als auch designbasierte Stichprobenverfahren wie Clusterstichprobe und geschichtete Stichprobe entwickelt. Jedes Kapitel wird mit der Umsetzung der Verfahren mit dem Programpaket R abgeschlossen. Hierdurch werden die Leserin und der Leser in die Lage versetzt, selbst komplexe Stichprobenverfahren direkt in R umzusetzen. Ein Ausblick auf weitere Verfahren und praktische Probleme schließt jedes Kapitel des Buches ab.
Stochastic Equations in Infinite Dimensions
by Giuseppe Da PratoThe aim of this book is to give a systematic and self-contained presentation of basic results on stochastic evolution equations in infinite dimensional, typically Hilbert and Banach, spaces. These are a generalization of stochastic differential equations as introduced by Itô and Gikham that occur, for instance, when describing random phenomena that crop up in science and engineering, as well as in the study of differential equations. The book is divided into three parts. In the first the authors give a self-contained exposition of the basic properties of probability measure on separable Banach and Hilbert spaces, as required later; they assume a reasonable background in probability theory and finite dimensional stochastic processes. The second part is devoted to the existence and uniqueness of solutions of a general stochastic evolution equation, and the third concerns the qualitative properties of those solutions. Appendices gather together background results from analysis that are otherwise hard to find under one roof. The book ends with a comprehensive bibliography that will contribute to the book's value for all working in stochastic differential equations.
Stochastic Analysis
by Hiroyuki Matsumoto Setsuo TaniguchiThanks to the driving forces of the It#65533; calculus and the Malliavin calculus, stochastic analysis has expanded into numerous fields including partial differential equations, physics, and mathematical finance. This book is a compact, graduate-level text that develops the two calculi in tandem, laying out a balanced toolbox for researchers and students in mathematics and mathematical finance. The book explores foundations and applications of the two calculi, including stochastic integrals and differential equations, and the distribution theory on Wiener space developed by the Japanese school of probability. Uniquely, the book then delves into the possibilities that arise by using the two flavors of calculus together. Taking a distinctive, path-space-oriented approach, this book crystallizes modern day stochastic analysis into a single volume.
Stochastic Analysis (Monographs in Mathematical Economics #3)
by Shigeo KusuokaThis book is intended for university seniors and graduate students majoring in probability theory or mathematical finance. In the first chapter, results in probability theory are reviewed. Then, it follows a discussion of discrete-time martingales, continuous time square integrable martingales (particularly, continuous martingales of continuous paths), stochastic integrations with respect to continuous local martingales, and stochastic differential equations driven by Brownian motions. In the final chapter, applications to mathematical finance are given. The preliminary knowledge needed by the reader is linear algebra and measure theory. Rigorous proofs are provided for theorems, propositions, and lemmas.In this book, the definition of conditional expectations is slightly different than what is usually found in other textbooks. For the Doob–Meyer decomposition theorem, only square integrable submartingales are considered, and only elementary facts of the square integrable functions are used in the proof. In stochastic differential equations, the Euler–Maruyama approximation is used mainly to prove the uniqueness of martingale problems and the smoothness of solutions of stochastic differential equations.
Stochastic Analysis Of Scaling Time Series: From Turbulence Theory to Applications
by François G. Schmitt Yongxiang HuangMulti-scale systems, involving complex interacting processes that occur over a range of temporal and spatial scales, are present in a broad range of disciplines. Several methodologies exist to retrieve this multi-scale information from a given time series; however, each method has its own limitations. This book presents the mathematical theory behind the stochastic analysis of scaling time series, including a general historical introduction to the problem of intermittency in turbulence, as well as how to implement this analysis for a range of different applications. Covering a variety of statistical methods, such as Fourier analysis and wavelet transforms, it provides readers with a thorough understanding of the techniques and when to apply them. New techniques to analyse stochastic processes, including empirical mode decomposition, are also explored. Case studies, in turbulence and ocean sciences, are used to demonstrate how these statistical methods can be applied in practice, for students and researchers.
Stochastic Analysis and Applications
by Mark A. PinskyThis volume attempts to exhibit current research in stochastic integration, stochastic differential equations, stochastic optimization and stochastic problems in physics and biology. It includes information on the theory of Dirichlet forms, Feynman integration and the Schrodinger's equation.
Stochastic Analysis and Applications 2014
by Dan Crisan Thaleia Zariphopoulou Ben HamblyArticles from many of the main contributors to recent progress in stochastic analysis are included in this volume, which provides a snapshot of the current state of the area and its ongoing developments. It constitutes the proceedings of the conference on "Stochastic Analysis and Applications" held at the University of Oxford and the Oxford-Man Institute during 23-27 September, 2013. The conference honored the 60th birthday of Professor Terry Lyons FLSW FRSE FRS, Wallis Professor of Mathematics, University of Oxford. Terry Lyons is one of the leaders in the field of stochastic analysis. His introduction of the notion of rough paths has revolutionized the field, both in theory and in practice. Stochastic Analysis is the branch of mathematics that deals with the analysis of dynamical systems affected by noise. It emerged as a core area of mathematics in the late 20th century and has subsequently developed into an important theory with a wide range of powerful and novel tools, and with impressive applications within and beyond mathematics. Many systems are profoundly affected by stochastic fluctuations and it is not surprising that the array of applications of Stochastic Analysis is vast and touches on many aspects of life. The present volume is intended for researchers and Ph. D. students in stochastic analysis and its applications, stochastic optimization and financial mathematics, as well as financial engineers and quantitative analysts.
Stochastic Analysis and Related Topics
by Fabrice Baudoin Jonathon PetersonThe articles in this collection are a sampling of some of the research presented during the conference "Stochastic Analysis and Related Topics," held in May of 2015 at Purdue University in honor of the 60thbirthday of Rodrigo Banuelos. A wide variety of topics in probability theory is covered in these proceedings, including heat kernel estimates, Malliavin calculus, rough paths differential equations, Levy processes, Brownian motion on manifolds, and spin glasses, among other topics.
Stochastic Analysis and Related Topics
by Laurent Decreusefond Jamal NajimSince the early eighties, Ali Süleyman Üstünel has been one of the main contributors to the field of Malliavin calculus. In a workshop held in Paris, June 2010 several prominent researchers gave exciting talks in honor of his 60th birthday. The present volume includes scientific contributions from this workshop. Probability theory is first and foremost aimed at solving real-life problems containing randomness. Markov processes are one of the key tools for modeling that plays a vital part concerning such problems. Contributions on inventory control, mutation-selection in genetics and public-private partnerships illustrate several applications in this volume. Stochastic differential equations, be they partial or ordinary, also play a key role in stochastic modeling. Two of the contributions analyze examples that share a focus on probabilistic tools, namely stochastic analysis and stochastic calculus. Three other papers are devoted more to the theoretical development of these aspects. The volume addresses graduate students and researchers interested in stochastic analysis and its applications.
Stochastic Analysis for Finance with Simulations
by Geon Ho Ho ChoeThis book is an introduction to stochastic analysis and quantitative finance; it includes both theoretical and computational methods. Topics covered are stochastic calculus, option pricing, optimal portfolio investment, and interest rate models. Also included are simulations of stochastic phenomena, numerical solutions of the Black-Scholes-Merton equation, Monte Carlo methods, and time series. Basic measure theory is used as a tool to describe probabilistic phenomena. The level of familiarity with computer programming is kept to a minimum. To make the book accessible to a wider audience, some background mathematical facts are included in the first part of the book and also in the appendices. This work attempts to bridge the gap between mathematics and finance by using diagrams, graphs and simulations in addition to rigorous theoretical exposition. Simulations are not only used as the computational method in quantitative finance, but they can also facilitate an intuitive and deeper understanding of theoretical concepts. Stochastic Analysis for Finance with Simulations is designed for readers who want to have a deeper understanding of the delicate theory of quantitative finance by doing computer simulations in addition to theoretical study. It will particularly appeal to advanced undergraduate and graduate students in mathematics and business, but not excluding practitioners in finance industry.
Stochastic Analysis for Gaussian Random Processes and Fields: With Applications (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)
by Vidyadhar S. Mandrekar Leszek GawareckiStochastic Analysis for Gaussian Random Processes and Fields: With Applications presents Hilbert space methods to study deep analytic properties connecting probabilistic notions. In particular, it studies Gaussian random fields using reproducing kernel Hilbert spaces (RKHSs).The book begins with preliminary results on covariance and associated RKHS
Stochastic Analysis for Poisson Point Processes
by Giovanni Peccati Matthias ReitznerStochastic geometry is the branchof mathematics that studies geometric structures associated with randomconfigurations, such as random graphs, tilings and mosaics. Due to its closeties with stereology and spatial statistics, the results in this area arerelevant for a large number of important applications, e. g. to the mathematicalmodeling and statistical analysis of telecommunication networks, geostatisticsand image analysis. In recent years - due mainly to the impetus of the authorsand their collaborators - a powerful connection has been established betweenstochastic geometry and the Malliavin calculus of variations, which is acollection of probabilistic techniques based on the properties ofinfinite-dimensional differential operators. This has led in particular to thediscovery of a large number of new quantitative limit theorems forhigh-dimensional geometric objects. This unique book presents anorganic collection of authoritative surveys written by the principal actors in thisrapidly evolving field, offering a rigorous yet lively presentation of its manyfacets.
Stochastic Analysis in Production Process and Ecology Under Uncertainty
by Bogusław BiedaThe monograph addresses a problem of stochastic analysis based on the uncertainty assessment by simulation and application of this method in ecology and steel industry under uncertainty. The first chapter defines the Monte Carlo (MC) method and random variables in stochastic models. Chapter two deals with the contamination transport in porous media. Stochastic approach for Municipal Solid Waste transit time contaminants modeling using MC simulation has been worked out. The third chapter describes the risk analysis of the waste to energy facility proposal for Konin city, including the financial aspects. Environmental impact assessment of the ArcelorMittal Steel Power Plant, in Kraków - in the chapter four - is given. Thus, four scenarios of the energy mix production processes were studied. Chapter five contains examples of using ecological Life Cycle Assessment (LCA) - a relatively new method of environmental impact assessment - which help in preparing pro-ecological strategy, and which can lead to reducing the amount of wastes produced in the ArcelorMittal Steel Plant production processes. Moreover, real input and output data of selected processes under uncertainty, mainly used in the LCA technique, have been examined. The last chapter of this monograph contains final summary. The log-normal probability distribution, widely used in risk analysis and environmental management, in order to develop a stochastic analysis of the LCA, as well as uniform distribution for stochastic approach of pollution transport in porous media has been proposed. The distributions employed in this monograph are assembled from site-specific data, data existing in the most current literature, and professional judgment.
Stochastic Analysis of Biochemical Systems
by David F. Anderson Thomas G. KurtzThis book focuses on counting processes and continuous-time Markov chains motivated by examples and applications drawn from chemical networks in systems biology. The book should serve well as a supplement for courses in probability and stochastic processes. While the material is presented in a manner most suitable for students who have studied stochastic processes up to and including martingales in continuous time, much of the necessary background material is summarized in the Appendix. Students and Researchers with a solid understanding of calculus, differential equations and elementary probability and who are well-motivated by the applications will find this book of interest. David F. Anderson is Associate Professor in the Department of Mathematics at the University of Wisconsin and Thomas G. Kurtz is Emeritus Professor in the Departments of Mathematics and Statistics at that university. Their research is focused on probability and stochastic processes with applications in biology and other areas of science and technology. These notes are based in part on lectures given by Professor Anderson at the University of Wisconsin - Madison and by Professor Kurtz at Goethe University Frankfurt.
Stochastic Approaches to Electron Transport in Micro- and Nanostructures (Modeling and Simulation in Science, Engineering and Technology)
by Ivan Dimov Siegfried Selberherr Mihail NedjalkovThe book serves as a synergistic link between the development of mathematical models and the emergence of stochastic (Monte Carlo) methods applied for the simulation of current transport in electronic devices. Regarding the models, the historical evolution path, beginning from the classical charge carrier transport models for microelectronics to current quantum-based nanoelectronics, is explicatively followed. Accordingly, the solution methods are elucidated from the early phenomenological single particle algorithms applicable for stationary homogeneous physical conditions up to the complex algorithms required for quantum transport, based on particle generation and annihilation. The book fills the gap between monographs focusing on the development of the theory and the physical aspects of models, their application, and their solution methods and monographs dealing with the purely theoretical approaches for finding stochastic solutions of Fredholm integral equations.
Stochastic Approximation: A Dynamical Systems Viewpoint (Texts and Readings in Mathematics #48)
by Vivek S. BorkarThis book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.
Stochastic Approximation: Second Edition (Texts and Readings in Mathematics #48)
by Vivek S. BorkarThis book serves as an advanced text for a graduate course on stochastic algorithms for graduate students in probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the “ordinary differential equation (ODE) approach” which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.
Stochastic Averaging and Stochastic Extremum Seeking
by Shu-Jun Liu Miroslav KrsticStochastic Averaging and Extremum Seeking treats methods inspired by attempts to understand the seemingly non-mathematical question of bacterial chemotaxis and their application in other environments. The text presents significant generalizations on existing stochastic averaging theory developed from scratch and necessitated by the need to avoid violation of previous theoretical assumptions by algorithms which are otherwise effective in treating these systems. Coverage is given to four main topics. Stochastic averaging theorems are developed for the analysis of continuous-time nonlinear systems with random forcing, removing prior restrictions on nonlinearity growth and on the finiteness of the time interval. The new stochastic averaging theorems are usable not only as approximation tools but also for providing stability guarantees. Stochastic extremum-seeking algorithms are introduced for optimization of systems without available models. Both gradient- and Newton-based algorithms are presented, offering the user the choice between the simplicity of implementation (gradient) and the ability to achieve a known, arbitrary convergence rate (Newton). The design of algorithms for non-cooperative/adversarial games is described. The analysis of their convergence to Nash equilibria is provided. The algorithms are illustrated on models of economic competition and on problems of the deployment of teams of robotic vehicles. Bacterial locomotion, such as chemotaxis in E. coli, is explored with the aim of identifying two simple feedback laws for climbing nutrient gradients. Stochastic extremum seeking is shown to be a biologically-plausible interpretation for chemotaxis. For the same chemotaxis-inspired stochastic feedback laws, the book also provides a detailed analysis of convergence for models of nonholonomic robotic vehicles operating in GPS-denied environments. The book contains block diagrams and several simulation examples, including examples arising from bacterial locomotion, multi-agent robotic systems, and economic market models. Stochastic Averaging and Extremum Seeking will be informative for control engineers from backgrounds in electrical, mechanical, chemical and aerospace engineering and to applied mathematicians. Economics researchers, biologists, biophysicists and roboticists will find the applications examples instructive.
Stochastic Averaging: Methods and Applications, Volume 1
by Wei-Qiu Zhu Mao-Lin Deng Guo-Qiang CaiThe stochastic averaging methods are among the most effective and widely applied approximate methods for studying nonlinear stochastic dynamics. Upon an overview of global research on the subject, the book highlights a comprehensive summary of research results obtained by the group led by Professor Weiqiu Zhu at Zhejiang University in China and the group led by Professors Y. K. Lin and G. Q. Cai at Florida Atlantic University in the USA over the past three decades. The books are structured to progress logically from foundational principles to simple problems and then to increasingly complex applications. To facilitate understanding and mastery of the methods, the books offer essential preliminary knowledge and a wealth of examples. The book comprises two volumes. Volume 1 introduces the basic principles of stochastic averaging methods and their applications to single-degree-of-freedom systems under various random excitations. It also covers stochastic averaging methods for quasi-Hamiltonian systems subjected to different random excitations, including Gaussian white noise, combined Gaussian and Poisson white noises, and fractional Gaussian noise. Volume 2 explores stochastic averaging methods for quasi-integrable Hamiltonian systems under colored noise excitation, quasi-integrable Hamiltonian systems with genetic effects under Gaussian white noise and colored noise excitations, and quasi-generalized Hamiltonian systems under Gaussian white noise excitation. Additionally, it covers applications of these methods in ecosystems and some other natural science and engineering scenarios. These books serve as both introductory texts and valuable reference resources for readers in higher education and research institutions who are interested in or actively engaged in research involving nonlinear stochastic dynamics. The fields covered include mechanics, physics, chemistry, biology, ecology, astronautics and aeronautics, oceanography, civil engineering, mechanical engineering, and electrical engineering.
Stochastic Benchmarking: Theory and Applications (International Series in Operations Research & Management Science #317)
by Vincent Charles Alireza Amirteimoori Biresh K. Sahoo Saber MehdizadehThis book introduces readers to benchmarking techniques in the stochastic environment, primarily stochastic data envelopment analysis (DEA), and provides stochastic models in DEA for the possibility of variations in inputs and outputs. It focuses on the application of theories and interpretations of the mathematical programs, which are combined with economic and organizational thinking. The book’s main purpose is to shed light on the advantages of the different methods in deterministic and stochastic environments and thoroughly prepare readers to properly use these methods in various cases. Simple examples, along with graphical illustrations and real-world applications in industry, are provided for a better understanding. The models introduced here can be easily used in both theoretical and real-world evaluations. This book is intended for graduate and PhD students, advanced consultants, and practitioners with an interest in quantitative performance evaluation.