ISBN: 978-1-119-30081-6
April 2019 500 Pages
Selected type: Hardcover
Probability, Random Variables, Statistics, and Random Processes: Fundamentals & Applications is a comprehensive undergraduate-level textbook. With its excellent topical coverage, the focus of this book is on the basic principles and practical applications of the fundamental concepts that are extensively used in various Engineering disciplines as well as in a variety of programs in Life and Social Sciences. The text provides students with the requisite building blocks of knowledge they require to understand and progress in their areas of interest. With a simple, clear-cut style of writing, the intuitive explanations, insightful examples, and practical applications are the hallmarks of this book.
The text consists of twelve chapters divided into four parts. Part-I, Probability (Chapters 1 ? 3), lays a solid groundwork for probability theory, and introduces applications in counting, gambling, reliability, and security. Part-II, Random Variables (Chapters 4 ? 7), discusses in detail multiple random variables, along with a multitude of frequently-encountered probability distributions. Part-III, Statistics (Chapters 8 ? 10), highlights estimation and hypothesis testing. Part-IV, Random Processes (Chapters 11 ? 12), delves into the characterization and processing of random processes. Other notable features include:
Most of the text assumes no knowledge of subject matter past first year calculus and linear algebra
With its independent chapter structure and rich choice of topics, a variety of syllabi for different courses at the junior, senior, and graduate levels can be supported
A supplemental website includes solutions to about 250 practice problems, lecture slides, and figures and tables from the text
Given its engaging tone, grounded approach, methodically-paced flow, thorough coverage, and flexible structure, Probability, Random Variables, Statistics, and Random Processes: Fundamentals & Applications clearly serves as a must textbook for courses not only in Electrical Engineering, but also in Computer Engineering, Software Engineering, and Computer Science.
Publication planned for: May 2019
availability: Not yet published - available from May 2019
format: Paperback
isbn: 9781316615553
Model theory begins with an audacious idea: to consider statements about mathematical structures as mathematical objects of study in their own right. While inherently important as a tool of mathematical logic, it also enjoys connections to and applications in diverse branches of mathematics, including algebra, number theory and analysis. Despite this, traditional introductions to model theory assume a graduate-level background of the reader. In this innovative textbook, Jonathan Kirby brings model theory to an undergraduate audience. The highlights of basic model theory are illustrated through examples from specific structures familiar from undergraduate mathematics, paying particular attention to definable sets throughout. With numerous exercises of varying difficulty, this is an accessible introduction to model theory and its place in mathematics.
Suitable for use as an undergraduate or masters level course in model theory, unlike traditional graduate-level texts.
Contains many exercises of varying difficulty, from bookwork to more substantial projects.
Presents model theory in the context of undergraduate mathematics via definable sets in familiar structures.
Part of Cambridge Monographs on Applied and Computational Mathematics
Publication planned for: May 2019
availability: Not yet published - available from May 2019
format: Hardback
isbn: 9781108480390
Mathematical and numerical modelling of the human cardiovascular system has attracted remarkable research interest due to its intrinsic mathematical difficulty and the increasing impact of cardiovascular diseases worldwide. This book addresses the two principal components of the cardiovascular system: arterial circulation and heart function. It systematically describes all aspects of the problem, stating the basic physical principles, analysing the associated mathematical models that comprise PDE and ODE systems, reviewing sound and efficient numerical methods for their approximation, and simulating both benchmark problems and clinically inspired problems. Mathematical modelling itself imposes tremendous challenges, due to the amazing complexity of the cardiovascular system and the need for computational methods that are stable, reliable and efficient. The final part is devoted to control and inverse problems, including parameter estimation, uncertainty quanti?cation and the development of reduced-order models that are important when solving problems with high complexity, which would otherwise be out of reach.
A solid foundation for applied mathematicians, bioengineers and computational scientists interested in modelling the cardiovascular system
Describes the most recent and efficient numerical methods for mathematical models
Examples of possible applications illustrate the relevance of the methods
Part of London Mathematical Society Lecture Note Series
Since the notion was introduced by Gromov in the 1980s, hyperbolicity of groups and spaces has played a significant role in geometric group theory; hyperbolic groups have good geometric properties that allow us to prove strong results. However, many classes of interest in our exploration of the universe of finitely generated groups contain examples that are not hyperbolic. Thus we wish to go gbeyond hyperbolicityh to find good generalisations that nevertheless permit similarly strong results. This book is the ideal resource for researchers wishing to contribute to this rich and active field. The first two parts are devoted to mini-courses and expository articles on coarse median spaces, semihyperbolicity, acylindrical hyperbolicity, Morse boundaries, and hierarchical hyperbolicity. These serve as an introduction for students and a reference for experts. The topics of the surveys (and more) re-appear in the research articles that make up Part III, presenting the latest results beyond hyperbolicity.
Mini-courses and expository articles serve as an introduction and as a reference on generalisations of Gromov hyperbolicity.
Short research articles on intriguing topics answer some interesting open questions.
Suitable for graduate students and established researchers alike.
December 20, 2018 Forthcoming
Reference - 226 Pages - 41 B/W Illustrations
ISBN 9781498773133 - CAT# K29543
Series: Chapman & Hall/CRC Interdisciplinary Statistics
Generalized Linear Models (GLMs) allow many statistical analyses to be extended to important statistical distributions other than the Normal distribution. While numerous books exist on how to analyse data using a GLM, little information is available on how to collect the data that are to be analysed in this way.
This is the first book focusing specifically on the design of experiments for GLMs. Much of the research literature on this topic is at a high mathematical level, and without any information on computation. This book explains the motivation behind various techniques, reduces the difficulty of the mathematics, or moves it to one side if it cannot be avoided, and gives examples of how to write and run computer programs using R.
The generalisation of the linear model to GLMs
Background mathematics, and the use of constrained optimisation in R
Coverage of the theory behind the optimality of a design
Individual chapters on designs for data that have Binomial or Poisson distributions
Bayesian experimental design
An online resource contains R programs used in the book
This book is aimed at readers who have done elementary differentiation
and understand minimal matrix algebra, and have familiarity with R. It
equips professional statisticians to read the research literature. Nonstatisticians
will be able to design their own experiments by following the examples
and using the programs provided.
Instructors
We provide complimentary e-inspection copies of primary textbooks to instructors considering our books for course adoption.
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