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Mathematical Analysis of Random Phenomena

Mathematical Analysis of Random Phenomena
Author: Ana Bela Ferreira Cruzeiro
Publisher: World Scientific
Total Pages: 241
Release: 2007
Genre: Mathematics
ISBN: 9812770542

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This volume highlights recent developments of stochastic analysis with a wide spectrum of applications, including stochastic differential equations, stochastic geometry, and nonlinear partial differential equations. While modern stochastic analysis may appear to be an abstract mixture of classical analysis and probability theory, this book shows that, in fact, it can provide versatile tools useful in many areas of applied mathematics where the phenomena being described are random. The geometrical aspects of stochastic analysis, often regarded as the most promising for applications, are specially investigated by various contributors to the volume.


Mathematical Analysis Of Random Phenomena - Proceedings Of The International Conference

Mathematical Analysis Of Random Phenomena - Proceedings Of The International Conference
Author: Ana Bela Cruzeiro
Publisher: World Scientific
Total Pages: 241
Release: 2007-04-04
Genre: Mathematics
ISBN: 9814475696

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This volume highlights recent developments of stochastic analysis with a wide spectrum of applications, including stochastic differential equations, stochastic geometry, and nonlinear partial differential equations.While modern stochastic analysis may appear to be an abstract mixture of classical analysis and probability theory, this book shows that, in fact, it can provide versatile tools useful in many areas of applied mathematics where the phenomena being described are random. The geometrical aspects of stochastic analysis, often regarded as the most promising for applications, are specially investigated by various contributors to the volume.


Random Phenomena

Random Phenomena
Author: Babatunde A. Ogunnaike
Publisher: CRC Press
Total Pages: 1061
Release: 2011-05-20
Genre: Technology & Engineering
ISBN: 1420044982

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Many of the problems that engineers face involve randomly varying phenomena of one sort or another. However, if characterized properly, even such randomness and the resulting uncertainty are subject to rigorous mathematical analysis. Taking into account the uniquely multidisciplinary demands of 21st-century science and engineering, Random Phenomena: Fundamentals of Probability and Statistics for Engineers provides students with a working knowledge of how to solve engineering problems that involve randomly varying phenomena. Basing his approach on the principle of theoretical foundations before application, Dr. Ogunnaike presents a classroom-tested course of study that explains how to master and use probability and statistics appropriately to deal with uncertainty in standard problems and those that are new and unfamiliar. Giving students the tools and confidence to formulate practical solutions to problems, this book offers many useful features, including: Unique case studies to illustrate the fundamentals and applications of probability and foster understanding of the random variable and its distribution Examples of development, selection, and analysis of probability models for specific random variables Presentation of core concepts and ideas behind statistics and design of experiments Selected "special topics," including reliability and life testing, quality assurance and control, and multivariate analysis As classic scientific boundaries continue to be restructured, the use of engineering is spilling over into more non-traditional areas, ranging from molecular biology to finance. This book emphasizes fundamentals and a "first principles" approach to deal with this evolution. It illustrates theory with practical examples and case studies, equipping readers to deal with a wide range of problems beyond those in the book. About the Author: Professor Ogunnaike is Interim Dean of Engineering at the University of Delaware. He is the recipient of the 2008 American Automatic Control Council's Control Engineering Practice Award, the ISA's Donald P. Eckman Education Award, the Slocomb Excellence in Teaching Award, and was elected into the US National Academy of Engineering in 2012.


Spontaneous Phenomena

Spontaneous Phenomena
Author:
Publisher: Elsevier
Total Pages: 195
Release: 2012-12-02
Genre: Science
ISBN: 0323160387

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Spontaneous Phenomena: A Mathematical Analysis covers certain aspects in the teaching of mathematics, including historical perspective, model-building, and the inner nature of mathematics. This book is organized into 12 chapters beginning with the development of the relevant mathematics and physics. This topic is followed by considerable chapters on the theoretical and statistical principles of mathematical analysis, with an emphasis on a model for a radioactive decay. Other chapters discuss various phenomena within biology, medicine, statistics of medicine, determination of age, traffic analysis, and other fields. The concluding chapters present the fundamentals of the Poisson approximation to the binomial distribution and the chi-square test for goodness of fit. This book is an ideal source for mathematics and physics pre-college and early college students.


Mathematical Modeling of Random and Deterministic Phenomena

Mathematical Modeling of Random and Deterministic Phenomena
Author: Solym Mawaki Manou-Abi
Publisher: John Wiley & Sons
Total Pages: 308
Release: 2020-04-28
Genre: Mathematics
ISBN: 1786304546

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This book highlights mathematical research interests that appear in real life, such as the study and modeling of random and deterministic phenomena. As such, it provides current research in mathematics, with applications in biological and environmental sciences, ecology, epidemiology and social perspectives. The chapters can be read independently of each other, with dedicated references specific to each chapter. The book is organized in two main parts. The first is devoted to some advanced mathematical problems regarding epidemic models; predictions of biomass; space-time modeling of extreme rainfall; modeling with the piecewise deterministic Markov process; optimal control problems; evolution equations in a periodic environment; and the analysis of the heat equation. The second is devoted to a modelization with interdisciplinarity in ecological, socio-economic, epistemological, demographic and social problems. Mathematical Modeling of Random and Deterministic Phenomena is aimed at expert readers, young researchers, plus graduate and advanced undergraduate students who are interested in probability, statistics, modeling and mathematical analysis.


Introductory Statistics and Random Phenomena

Introductory Statistics and Random Phenomena
Author: Manfred Denker
Publisher: Springer Science & Business Media
Total Pages: 550
Release: 1998-11-01
Genre: Mathematics
ISBN: 9780817640316

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Integrates traditional statistical data analysis with new computational experimentation capabilities and concepts of algorithmic complexity and chaotic behavior in nonlinear dynamic systems, offering tools for the study of random phenomena occurring in engineering and the natural, life, and social sciences. Each chapter presents experiments, exercises, and projects using the Mathematica Uncertain Virtual Worlds software packages. Large and original real-life data sets are introduced and analyzed as a model for independent study. Includes brief tutorials on using Mathematica programs. Intended as a text for an introductory level statistics course. Prerequisites include calculus and basic computer programming. Annotation copyrighted by Book News, Inc., Portland, OR


Introductory Statistics and Random Phenomena

Introductory Statistics and Random Phenomena
Author: Manfred Denker
Publisher: Birkhäuser
Total Pages: 521
Release: 2017-09-16
Genre: Computers
ISBN: 3319661523

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This textbook integrates traditional statistical data analysis with new computational experimentation capabilities and concepts of algorithmic complexity and chaotic behavior in nonlinear dynamic systems. This was the first advanced text/reference to bring together such a comprehensive variety of tools for the study of random phenomena occurring in engineering and the natural, life, and social sciences. The crucial computer experiments are conducted using the readily available computer program Mathematica® Uncertain Virtual WorldsTM software packages which optimize and facilitate the simulation environment. Brief tutorials are included that explain how to use the Mathematica® programs for effective simulation and computer experiments. Large and original real-life data sets are introduced and analyzed as a model for independent study. This is an excellent classroom tool and self-study guide. The material is presented in a clear and accessible style providing numerous exercises and bibliographical notes suggesting further reading. Topics and Features Comprehensive and integrated treatment of uncertainty arising in engineering and scientific phenomena – algorithmic complexity, statistical independence, and nonlinear chaotic behavior Extensive exercise sets, examples, and Mathematica® computer experiments that reinforce concepts and algorithmic methods Thorough presentation of methods of data compression and representation Algorithmic approach to model selection and design of experiments Large data sets and 13 Mathematica®-based Uncertain Virtual WorldsTM programs and code This text is an excellent resource for all applied statisticians, engineers, and scientists who need to use modern statistical analysis methods to investigate and model their data. The present, softcover reprint is designed to make this classic textbook available to a wider audience.


Theory and Simulation of Random Phenomena

Theory and Simulation of Random Phenomena
Author: Ettore Vitali
Publisher: Springer
Total Pages: 235
Release: 2018-06-13
Genre: Science
ISBN: 3319905155

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The purpose of this book is twofold: first, it sets out to equip the reader with a sound understanding of the foundations of probability theory and stochastic processes, offering step-by-step guidance from basic probability theory to advanced topics, such as stochastic differential equations, which typically are presented in textbooks that require a very strong mathematical background. Second, while leading the reader on this journey, it aims to impart the knowledge needed in order to develop algorithms that simulate realistic physical systems. Connections with several fields of pure and applied physics, from quantum mechanics to econophysics, are provided. Furthermore, the inclusion of fully solved exercises will enable the reader to learn quickly and to explore topics not covered in the main text. The book will appeal especially to graduate students wishing to learn how to simulate physical systems and to deepen their knowledge of the mathematical framework, which has very deep connections with modern quantum field theory.


The Statistical Stability Phenomenon

The Statistical Stability Phenomenon
Author: Igor I. Gorban
Publisher: Springer
Total Pages: 349
Release: 2016-10-17
Genre: Technology & Engineering
ISBN: 331943585X

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This monograph investigates violations of statistical stability of physical events, variables, and processes and develops a new physical-mathematical theory taking into consideration such violations – the theory of hyper-random phenomena. There are five parts. The first describes the phenomenon of statistical stability and its features, and develops methods for detecting violations of statistical stability, in particular when data is limited. The second part presents several examples of real processes of different physical nature and demonstrates the violation of statistical stability over broad observation intervals. The third part outlines the mathematical foundations of the theory of hyper-random phenomena, while the fourth develops the foundations of the mathematical analysis of divergent and many-valued functions. The fifth part contains theoretical and experimental studies of statistical laws where there is violation of statistical stability. The monograph should be of particular interest to engineers and scientists in general who study the phenomenon of statistical stability and use statistical methods for high-precision measurements, prediction, and signal processing over long observation intervals.