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Invariant Descriptive Set Theory

Invariant Descriptive Set Theory

Presents Results from a Very Active Area of ResearchExploring an active area of mathematics that studies the complexity of equivalence relations and classification problems Invariant Descriptive Set Theory presents an introduction to the basic concepts methods and results of this theory. It brings together techniques from various areas of mathematics such as algebra topology and logic which have diverse applications to other fields. After reviewing classical and effective descriptive set theory the text studies Polish groups and their actions. It then covers Borel reducibility results on Borel orbit and general definable equivalence relations. The author also provides proofs for numerous fundamental results such as the Glimm–Effros dichotomy the Burgess trichotomy theorem and the Hjorth turbulence theorem. The next part describes connections with the countable model theory of infinitary logic along with Scott analysis and the isomorphism relation on natural classes of countable models such as graphs trees and groups. The book concludes with applications to classification problems and many benchmark equivalence relations. By illustrating the relevance of invariant descriptive set theory to other fields of mathematics this self-contained book encourages readers to further explore this very active area of research.

GBP 59.99
1

Knot Projections

Knot Projections

Knot Projections offers a comprehensive overview of the latest methods in the study of this branch of topology based on current research inspired by Arnold’s theory of plane curves Viro’s quantization of the Arnold invariant and Vassiliev’s theory of knots among others. The presentation exploits the intuitiveness of knot projections to introduce the material to an audience without a prior background in topology making the book suitable as a useful alternative to standard textbooks on the subject. However the main aim is to serve as an introduction to an active research subject and includes many open questions.

GBP 44.99
1

Fortran 2018 with Parallel Programming

Fortran 2018 with Parallel Programming

The programming language Fortran dates back to 1957 when a team of IBM engineers released the first Fortran Compiler. During the past 60 years the language had been revised and updated several times to incorporate more features to enable writing clean and structured computer programs. The present version is Fortran 2018. Since the dawn of the computer era there had been a constant demand for a “larger” and “faster” machine. To increase the speed there are three hurdles. The density of the active components on a VLSI chip cannot be increased indefinitely and with the increase of the density heat dissipation becomes a major problem. Finally the speed of any signal cannot exceed the velocity of the light. However by using several inexpensive processors in parallel coupled with specialized software and hardware programmers can achieve computing speed similar to a supercomputer. This book can be used to learn the modern Fortran from the beginning and the technique of developing parallel programs using Fortran. It is for anyone who wants to learn Fortran. Knowledge beyond high school mathematics is not required. There is not another book on the market yet which deals with Fortran 2018 as well as parallel programming. FEATURES Descriptions of majority of Fortran 2018 instructions Numerical Model String with Variable Length IEEE Arithmetic and Exceptions Dynamic Memory Management Pointers Bit handling C-Fortran Interoperability Object Oriented Programming Parallel Programming using Coarray Parallel Programming using OpenMP Parallel Programming using Message Passing Interface (MPI) THE AUTHOR Dr Subrata Ray is a retired Professor Indian Association for the Cultivation of Science Kolkata. | Fortran 2018 with Parallel Programming

GBP 140.00
1

Beyond First Order Model Theory Volume I and II

Beyond First Order Model Theory Volume I and II

Model theory is the meta-mathematical study of the concept of mathematical truth. After Afred Tarski coined the term Theory of Models in the early 1950’s it rapidly became one of the central most active branches of mathematical logic. In the last few decades ideas that originated within model theory have provided powerful tools to solve problems in a variety of areas of classical mathematics including algebra combinatorics geometry number theory and Banach space theory and operator theory. The two volumes of Beyond First Order Model Theory present the reader with a fairly comprehensive vista rich in width and depth of some of the most active areas of contemporary research in model theory beyond the realm of the classical first-order viewpoint. Each chapter is intended to serve both as an introduction to a current direction in model theory and as a presentation of results that are not available elsewhere. All the articles are written so that they can be studied independently of one another. The first volume is an introduction to current trends in model theory and contains a collection of articles authored by top researchers in the field. It is intended as a reference for students as well as senior researchers. This second volume contains introductions to real-valued logic and applications abstract elementary classes and applications interconnections between model theory and function spaces nonstucture theory and model theory of second-order logic. Features A coherent introduction to current trends in model theory. Contains articles by some of the most influential logicians of the last hundred years. No other publication brings these distinguished authors together. Suitable as a reference for advanced undergraduate postgraduates and researchers. Material presented in the book (e. g abstract elementary classes first-order logics with dependent sorts and applications of infinitary logics in set theory) is not easily accessible in the current literature. The various chapters in the book can be studied independently. | Beyond First Order Model Theory Volume I and II

GBP 230.00
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Error Correcting Codes A Mathematical Introduction

Error Correcting Codes A Mathematical Introduction

Assuming little previous mathematical knowledge Error Correcting Codes provides a sound introduction to key areas of the subject. Topics have been chosen for their importance and practical significance which Baylis demonstrates in a rigorous but gentle mathematical style. Coverage includes optimal codes; linear and non-linear codes; general techniques of decoding errors and erasures; error detection; syndrome decoding and much more. Error Correcting Codes contains not only straight maths but also exercises on more investigational problem solving. Chapters on number theory and polynomial algebra are included to support linear codes and cyclic codes and an extensive reminder of relevant topics in linear algebra is given. Exercises are placed within the main body of the text to encourage active participation by the reader with comprehensive solutions provided. Error Correcting Codes will appeal to undergraduate students in pure and applied mathematical fields software engineering communications engineering computer science and information technology and to organizations with substantial research and development in those areas. | Error Correcting Codes A Mathematical Introduction

GBP 180.00
1

Data Science A First Introduction

Data Science A First Introduction

Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning create effective visualizations and extract insights from data using classification regression clustering and inference. The text emphasizes workflows that are clear reproducible and shareable and includes coverage of the basics of version control. All source code is available online demonstrating the use of good reproducible project workflows. Based on educational research and active learning principles the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive self-directed learning. The book will leave readers well-prepared for data science projects. The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia’s DSCI100: Introduction to Data Science course. | Data Science A First Introduction

GBP 48.99
1

Introductory Analysis An Inquiry Approach

Introductory Analysis An Inquiry Approach

Introductory Analysis: An Inquiry Approach aims to provide a self-contained inquiry-oriented approach to undergraduate-level real analysis. The presentation of the material in the book is intended to be inquiry-oriented' in that as each major topic is discussed details of the proofs are left to the student in a way that encourages an active approach to learning. The book is self-contained in two major ways: it includes scaffolding (i. e. brief guiding prompts marked as Key Steps in the Proof) for many of the theorems. Second it includes preliminary material that introduces students to the fundamental framework of logical reasoning and proof-writing techniques. Students will be able to use the guiding prompts (and refer to the preliminary work) to develop their proof-writing skills. FeaturesStructured in such a way that approximately one week of class can be devoted to each chapterSuitable as a primary text for undergraduates or as a supplementary text for some postgraduate coursesStrikes a unique balance between enquiry-based learning and more traditional approaches to teaching | Introductory Analysis An Inquiry Approach

GBP 44.99
1

Discovering Evolution Equations with Applications Volume 1-Deterministic Equations

Discovering Evolution Equations with Applications Volume 1-Deterministic Equations

Discovering Evolution Equations with Applications: Volume 1-Deterministic Equations provides an engaging accessible account of core theoretical results of evolution equations in a way that gradually builds intuition and culminates in exploring active research. It gives nonspecialists even those with minimal prior exposure to analysis the foundation to understand what evolution equations are and how to work with them in various areas of practice. After presenting the essentials of analysis the book discusses homogenous finite-dimensional ordinary differential equations. Subsequent chapters then focus on linear homogenous abstract nonhomogenous linear semi-linear functional Sobolev-type neutral delay and nonlinear evolution equations. The final two chapters explore research topics including nonlocal evolution equations. For each class of equations the author develops a core of theoretical results concerning the existence and uniqueness of solutions under various growth and compactness assumptions continuous dependence upon initial data and parameters convergence results regarding the initial data and elementary stability results. By taking an applications-oriented approach this self-contained conversational-style book motivates readers to fully grasp the mathematical details of studying evolution equations. It prepares newcomers to successfully navigate further research in the field. | Discovering Evolution Equations with Applications Volume 1-Deterministic Equations

GBP 74.99
1

Algorithmic Trading and Quantitative Strategies

Algorithmic Trading and Quantitative Strategies

Algorithmic Trading and Quantitative Strategies provides an in-depth overview of this growing field with a unique mix of quantitative rigor and practitioner’s hands-on experience. The focus on empirical modeling and practical know-how makes this book a valuable resource for students and professionals. The book starts with the often overlooked context of why and how we trade via a detailed introduction to market structure and quantitative microstructure models. The authors then present the necessary quantitative toolbox including more advanced machine learning models needed to successfully operate in the field. They next discuss the subject of quantitative trading alpha generation active portfolio management and more recent topics like news and sentiment analytics. The last main topic of execution algorithms is covered in detail with emphasis on the state of the field and critical topics including the elusive concept of market impact. The book concludes with a discussion of the technology infrastructure necessary to implement algorithmic strategies in large-scale production settings. A GitHub repository includes data sets and explanatory/exercise Jupyter notebooks. The exercises involve adding the correct code to solve the particular analysis/problem.

GBP 99.99
1

Sequence Space Theory with Applications

Sequence Space Theory with Applications

The book features original chapters on sequence spaces involving the idea of ideal convergence modulus function multiplier sequences Riesz mean Fibonacci difference matrix etc. and illustrate their involvement in various applications. The preliminaries have been presented in the beginning of each chapter and then the advanced discussion takes place so it is useful for both expert and nonexpert on aforesaid topics. The book consists of original thirteen research chapters contributed by the well-recognized researchers in the field of sequence spaces with associated applications. Features Discusses the Fibonacci and vector valued difference sequence spaces Presents the solution of Volterra integral equation in Banach algebra Discusses some sequence spaces involving invariant mean and related to the domain of Jordan totient matrix Presents the Tauberian theorems of double sequences Discusses the paranormed Riesz difference sequence space of fractional order Includes a technique for studying the existence of solutions of infinite system of functional integro-differential equations in Banach sequence spaces The subject of book is an active area of research of present time internationally and would serve as a good source for researcher and educators involved with the topic of sequence spaces. | Sequence Space Theory with Applications

GBP 150.00
1

Handbook of Computational Group Theory

Handbook of Computational Group Theory

The origins of computation group theory (CGT) date back to the late 19th and early 20th centuries. Since then the field has flourished particularly during the past 30 to 40 years and today it remains a lively and active branch of mathematics. The Handbook of Computational Group Theory offers the first complete treatment of all the fundamental methods and algorithms in CGT presented at a level accessible even to advanced undergraduate students. It develops the theory of algorithms in full detail and highlights the connections between the different aspects of CGT and other areas of computer algebra. While acknowledging the importance of the complexity analysis of CGT algorithms the authors' primary focus is on algorithms that perform well in practice rather than on those with the best theoretical complexity. Throughout the book applications of all the key topics and algorithms to areas both within and outside of mathematics demonstrate how CGT fits into the wider world of mathematics and science. The authors include detailed pseudocode for all of the fundamental algorithms and provide detailed worked examples that bring the theorems and algorithms to life.

GBP 44.99
1

Data Classification Algorithms and Applications

Data Classification Algorithms and Applications

Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition database data mining and machine learning. Addressing the work of these different communities in a unified way Data Classification: Algorithms and Applications explores the underlying algorithms of classification as well as applications of classification in a variety of problem domains including text multimedia social network and biological data. This comprehensive book focuses on three primary aspects of data classification:Methods: The book first describes common techniques used for classification including probabilistic methods decision trees rule-based methods instance-based methods support vector machine methods and neural networks. Domains: The book then examines specific methods used for data domains such as multimedia text time-series network discrete sequence and uncertain data. It also covers large data sets and data streams due to the recent importance of the big data paradigm. Variations: The book concludes with insight on variations of the classification process. It discusses ensembles rare-class learning distance function learning active learning visual learning transfer learning and semi-supervised learning as well as evaluation aspects of classifiers. | Data Classification Algorithms and Applications

GBP 44.99
1

Joint Modeling of Longitudinal and Time-to-Event Data

Joint Modeling of Longitudinal and Time-to-Event Data

Longitudinal studies often incur several problems that challenge standard statistical methods for data analysis. These problems include non-ignorable missing data in longitudinal measurements of one or more response variables informative observation times of longitudinal data and survival analysis with intermittently measured time-dependent covariates that are subject to measurement error and/or substantial biological variation. Joint modeling of longitudinal and time-to-event data has emerged as a novel approach to handle these issues. Joint Modeling of Longitudinal and Time-to-Event Data provides a systematic introduction and review of state-of-the-art statistical methodology in this active research field. The methods are illustrated by real data examples from a wide range of clinical research topics. A collection of data sets and software for practical implementation of the joint modeling methodologies are available through the book website. This book serves as a reference book for scientific investigators who need to analyze longitudinal and/or survival data as well as researchers developing methodology in this field. It may also be used as a textbook for a graduate level course in biostatistics or statistics.

GBP 46.99
1

Combinatorics of Compositions and Words

Combinatorics of Compositions and Words

A One-Stop Source of Known Results a Bibliography of Papers on the Subject and Novel Research Directions Focusing on a very active area of research in the last decade Combinatorics of Compositions and Words provides an introduction to the methods used in the combinatorics of pattern avoidance and pattern enumeration in compositions and words. It also presents various tools and approaches that are applicable to other areas of enumerative combinatorics. After a historical perspective on research in the area the text introduces techniques to solve recurrence relations including iteration and generating functions. It then focuses on enumeration of basic statistics for compositions. The text goes on to present results on pattern avoidance for subword subsequence and generalized patterns in compositions and then applies these results to words. The authors also cover automata the ECO method generating trees and asymptotic results via random compositions and complex analysis. Highlighting both established and new results this book explores numerous tools for enumerating patterns in compositions and words. It includes a comprehensive bibliography and incorporates the use of the computer algebra systems Maple™ and Mathematica® as well as C++ to perform computations.

GBP 74.99
1

Surrogates Gaussian Process Modeling Design and Optimization for the Applied Sciences

Surrogates Gaussian Process Modeling Design and Optimization for the Applied Sciences

Surrogates: a graduate textbook or professional handbook on topics at the interface between machine learning spatial statistics computer simulation meta-modeling (i. e. emulation) design of experiments and optimization. Experimentation through simulation human out-of-the-loop statistical support (focusing on the science) management of dynamic processes online and real-time analysis automation and practical application are at the forefront. Topics include:Gaussian process (GP) regression for flexible nonparametric and nonlinear modeling. Applications to uncertainty quantification sensitivity analysis calibration of computer models to field data sequential design/active learning and (blackbox/Bayesian) optimization under uncertainty. Advanced topics include treed partitioning local GP approximation modeling of simulation experiments (e. g. agent-based models) with coupled nonlinear mean and variance (heteroskedastic) models. Treatment appreciates historical response surface methodology (RSM) and canonical examples but emphasizes contemporary methods and implementation in R at modern scale. Rmarkdown facilitates a fully reproducible tour complete with motivation from application to and illustration with compelling real-data examples. Presentation targets numerically competent practitioners in engineering physical and biological sciences. Writing is statistical in form but the subjects are not about statistics. Rather they’re about prediction and synthesis under uncertainty; about visualization and information design and decision making computing and clean code. | Surrogates Gaussian Process Modeling Design and Optimization for the Applied Sciences

GBP 38.99
1

Discrete Mathematics with Ducks

Discrete Mathematics with Ducks

Discrete Mathematics with Ducks Second Edition is a gentle introduction for students who find the proofs and abstractions of mathematics challenging. At the same time it provides stimulating material that instructors can use for more advanced students. The first edition was widely well received with its whimsical writing style and numerous exercises and materials that engaged students at all levels. The new expanded edition continues to facilitate effective and active learning. It is designed to help students learn about discrete mathematics through problem-based activities. These are created to inspire students to understand mathematics by actively practicing and doing which helps students better retain what they’ve learned. As such each chapter contains a mixture of discovery-based activities projects expository text in-class exercises and homework problems. The author’s lively and friendly writing style is appealing to both instructors and students alike and encourages readers to learn. The book’s light-hearted approach to the subject is a guiding principle and helps students learn mathematical abstraction. Features:The book’s Try This! sections encourage students to construct components of discussed concepts theorems and proofsProvided sets of discovery problems and illustrative examples reinforce learningBonus sections can be used by instructors as part of their regular curriculum for projects or for further study

GBP 38.99
1

Handbook of Mixture Analysis

Handbook of Mixture Analysis

Mixture models have been around for over 150 years and they are found in many branches of statistical modelling as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate continuous or categorical cross-sectional time series networks and much more. Mixture analysis is a very active research topic in statistics and machine learning with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very timely publication presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics including the EM algorithm Bayesian mixture models model-based clustering high-dimensional data hidden Markov models and applications in finance genomics and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data together with computational implementation to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field whether they are developing new methodology or applying the models to real scientific problems.

GBP 56.99
1

Handbook of Cluster Analysis

Handbook of Cluster Analysis

Handbook of Cluster Analysis provides a comprehensive and unified account of the main research developments in cluster analysis. Written by active distinguished researchers in this area the book helps readers make informed choices of the most suitable clustering approach for their problem and make better use of existing cluster analysis tools. The book is organized according to the traditional core approaches to cluster analysis from the origins to recent developments. After an overview of approaches and a quick journey through the history of cluster analysis the book focuses on the four major approaches to cluster analysis. These approaches include methods for optimizing an objective function that describes how well data is grouped around centroids dissimilarity-based methods mixture models and partitioning models and clustering methods inspired by nonparametric density estimation. The book also describes additional approaches to cluster analysis including constrained and semi-supervised clustering and explores other relevant issues such as evaluating the quality of a cluster. This handbook is accessible to readers from various disciplines reflecting the interdisciplinary nature of cluster analysis. For those already experienced with cluster analysis the book offers a broad and structured overview. For newcomers to the field it presents an introduction to key issues. For researchers who are temporarily or marginally involved with cluster analysis problems the book gives enough algorithmic and practical details to facilitate working knowledge of specific clustering areas.

GBP 66.99
1

Recent Advances and Applications of Fuzzy Metric Fixed Point Theory

Recent Advances and Applications of Fuzzy Metric Fixed Point Theory

This book not only presents essential material to understand fuzzy metric fixed point theory but also enables the readers to appreciate the recent advancements made in this direction. It contains seven chapters on different topics in fuzzy metric fixed point theory. These chapters cover a good range of interesting topics such as con- vergence problems in fuzzy metrics fixed figure problems and applications of fuzzy metrics. The main focus is to unpack a number of diverse aspects of fuzzy metric fixed point theory and its applications in an understandable way so that it could help and motivate young graduates to explore new avenues of research to extend this flourishing area in different directions. The discussion on fixed figure problems and fuzzy contractive fixed point theorems and their different generalizations invites active researchers in this field to develop a new branch of fixed point theory. Features: Explore the latest research and developments in fuzzy metric fixed point theory. Describes applications of fuzzy metrics to colour image processing. Covers new topics on fuzzy fixed figure problems. Filled with examples and open problems. This book serves as a reference book for scientific investigators who want to analyze a simple and direct presentation of the fundamentals of the theory of fuzzy metric fixed point and its applications. It may also be used as a textbook for postgraduate and research students who try to derive future research scope in this area. | Recent Advances and Applications of Fuzzy Metric Fixed Point Theory

GBP 150.00
1

Introduction to Self-Driving Vehicle Technology

Introduction to Self-Driving Vehicle Technology

This book aims to teach the core concepts that make Self-driving vehicles (SDVs) possible. It is aimed at people who want to get their teeth into self-driving vehicle technology by providing genuine technical insights where other books just skim the surface. The book tackles everything from sensors and perception to functional safety and cybersecurity. It also passes on some practical know-how and discusses concrete SDV applications along with a discussion of where this technology is heading. It will serve as a good starting point for software developers or professional engineers who are eager to pursue a career in this exciting field and want to learn more about the basics of SDV algorithms. Likewise academic researchers technology enthusiasts and journalists will also find the book useful. Key Features: Offers a comprehensive technological walk-through of what really matters in SDV development: from hardware software to functional safety and cybersecurity Written by an active practitioner with extensive experience in series development and research in the fields of Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Covers theoretical fundamentals of state-of-the-art SLAM multi-sensor data fusion and other SDV algorithms. Includes practical information and hands-on material with Robot Operating System (ROS) and Open Source Car Control (OSCC). Provides an overview of the strategies trends and applications which companies are pursuing in this field at present as well as other technical insights from the industry. | Introduction to Self-Driving Vehicle Technology

GBP 48.99
1

Introduction to Mathematical Oncology

Introduction to Mathematical Oncology

Introduction to Mathematical Oncology presents biologically well-motivated and mathematically tractable models that facilitate both a deep understanding of cancer biology and better cancer treatment designs. It covers the medical and biological background of the diseases modeling issues and existing methods and their limitations. The authors introduce mathematical and programming tools along with analytical and numerical studies of the models. They also develop new mathematical tools and look to future improvements on dynamical models. After introducing the general theory of medicine and exploring how mathematics can be essential in its understanding the text describes well-known practical and insightful mathematical models of avascular tumor growth and mathematically tractable treatment models based on ordinary differential equations. It continues the topic of avascular tumor growth in the context of partial differential equation models by incorporating the spatial structure and physiological structure such as cell size. The book then focuses on the recent active multi-scale modeling efforts on prostate cancer growth and treatment dynamics. It also examines more mechanistically formulated models including cell quota-based population growth models with applications to real tumors and validation using clinical data. The remainder of the text presents abundant additional historical biological and medical background materials for advanced and specific treatment modeling efforts. Extensively classroom-tested in undergraduate and graduate courses this self-contained book allows instructors to emphasize specific topics relevant to clinical cancer biology and treatment. It can be used in a variety of ways including a single-semester undergraduate course a more ambitious graduate course or a full-year sequence on mathematical oncology.

GBP 44.99
1

Explorations in Computing An Introduction to Computer Science and Python Programming

Explorations in Computing An Introduction to Computer Science and Python Programming

An Active Learning Approach to Teaching the Main Ideas in Computing Explorations in Computing: An Introduction to Computer Science and Python Programming teaches computer science students how to use programming skills to explore fundamental concepts and computational approaches to solving problems. Tbook gives beginning students an introduction to computer science concepts and computer programming. Designed for CS0 and CS1 courses it is very well suited for alternative lecture styles including flipped classrooms. Prepares Students for Advanced Work in Computer ScienceA revised and updated version of the author’s Explorations in Computing: An Introduction to Computer Science this text incorporates two major differences. It now uses Python instead of Ruby as the lab software so that students can seamlessly transition from introductory projects to more advanced studies in later courses. The book also introduces Python programming providing students with sufficient programming skills so they can implement their own programs. Practical Step-by-Step ProjectsThe interactive lab projects in each chapter allow students to examine important ideas in computer science particularly how algorithms offer computational solutions to problems. Students can type expressions view results and run experiments that help them understand the concepts in a hands-on way. Web ResourcesThe Python software modules for each lab project are available on the author’s website. The modules include data files and sample Python code that students can copy and modify. In addition the site provides a lab manual of installation instructions and tips for editing programs and running commands in a terminal emulator. | Explorations in Computing An Introduction to Computer Science and Python Programming

GBP 46.99
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Encyclopedia of Knot Theory

Encyclopedia of Knot Theory

Knot theory is a fascinating mathematical subject with multiple links to theoretical physics. This enyclopedia is filled with valuable information on a rich and fascinating subject. – Ed Witten Recipient of the Fields Medal I spent a pleasant afternoon perusing the Encyclopedia of Knot Theory. It’s a comprehensive compilation of clear introductions to both classical and very modern developments in the field. It will be a terrific resource for the accomplished researcher and will also be an excellent way to lure students both graduate and undergraduate into the field. – Abigail Thompson Distinguished Professor of Mathematics at University of California Davis Knot theory has proven to be a fascinating area of mathematical research dating back about 150 years. Encyclopedia of Knot Theory provides short interconnected articles on a variety of active areas in knot theory and includes beautiful pictures deep mathematical connections and critical applications. Many of the articles in this book are accessible to undergraduates who are working on research or taking an advanced undergraduate course in knot theory. More advanced articles will be useful to graduate students working on a related thesis topic to researchers in another area of topology who are interested in current results in knot theory and to scientists who study the topology and geometry of biopolymers. Features Provides material that is useful and accessible to undergraduates postgraduates and full-time researchers Topics discussed provide an excellent catalyst for students to explore meaningful research and gain confidence and commitment to pursuing advanced degrees Edited and contributed by top researchers in the field of knot theory

GBP 47.95
1

Discovering Evolution Equations with Applications Volume 2-Stochastic Equations

Discovering Evolution Equations with Applications Volume 2-Stochastic Equations

Most existing books on evolution equations tend either to cover a particular class of equations in too much depth for beginners or focus on a very specific research direction. Thus the field can be daunting for newcomers to the field who need access to preliminary material and behind-the-scenes detail. Taking an applications-oriented conversational approach Discovering Evolution Equations with Applications: Volume 2-Stochastic Equations provides an introductory understanding of stochastic evolution equations. The text begins with hands-on introductions to the essentials of real and stochastic analysis. It then develops the theory for homogenous one-dimensional stochastic ordinary differential equations (ODEs) and extends the theory to systems of homogenous linear stochastic ODEs. The next several chapters focus on abstract homogenous linear nonhomogenous linear and semi-linear stochastic evolution equations. The author also addresses the case in which the forcing term is a functional before explaining Sobolev-type stochastic evolution equations. The last chapter discusses several topics of active research. Each chapter starts with examples of various models. The author points out the similarities of the models develops the theory involved and then revisits the examples to reinforce the theoretical ideas in a concrete setting. He incorporates a substantial collection of questions and exercises throughout the text and provides two layers of hints for selected exercises at the end of each chapter. Suitable for readers unfamiliar with analysis even at the undergraduate level this book offers an engaging and accessible account of core theoretical results of stochastic evolution equations in a way that gradually builds readers’ intuition. | Discovering Evolution Equations with Applications Volume 2-Stochastic Equations

GBP 69.99
1

Data Mining with R Learning with Case Studies Second Edition

Data Mining with R Learning with Case Studies Second Edition

Data Mining with R: Learning with Case Studies Second Edition uses practical examples to illustrate the power of R and data mining. Providing an extensive update to the best-selling first edition this new edition is divided into two parts. The first part will feature introductory material including a new chapter that provides an introduction to data mining to complement the already existing introduction to R. The second part includes case studies and the new edition strongly revises the R code of the case studies making it more up-to-date with recent packages that have emerged in R. The book does not assume any prior knowledge about R. Readers who are new to R and data mining should be able to follow the case studies and they are designed to be self-contained so the reader can start anywhere in the document. The book is accompanied by a set of freely available R source files that can be obtained at the book’s web site. These files include all the code used in the case studies and they facilitate the do-it-yourself approach followed in the book. Designed for users of data analysis tools as well as researchers and developers the book should be useful for anyone interested in entering the world of R and data mining. About the AuthorLuís Torgo is an associate professor in the Department of Computer Science at the University of Porto in Portugal. He teaches Data Mining in R in the NYU Stern School of Business’ MS in Business Analytics program. An active researcher in machine learning and data mining for more than 20 years Dr. Torgo is also a researcher in the Laboratory of Artificial Intelligence and Data Analysis (LIAAD) of INESC Porto LA. | Data Mining with R Learning with Case Studies Second Edition

GBP 44.99
1