Introduction to Stochastic Programming

More Do-It-Yourself Java Games: An Introduction to Java Graphics and Event-Driven Programming is the second book of the Do-It-Yourself Java Games series. In event-driven programming, the program lays

Software is pervasive in our lives. We are accustomed to dealing with the failures of much of that software - restarting an application is a very familiar solution. Such solutions are unacceptable when the software controls our cars, airplanes and medical devices or manages our private information. These applications must run without error. SPARK provides a means, based on mathematical proof, to guarantee that a program has no errors. SPARK is a formally defined programming language and a set of verification tools specifically designed to support the development of software used in high integrity applications. Using SPARK, developers can formally verify properties of their code such as information flow, freedom from runtime errors, functional correctness, security properties and safety properties. Written by two SPARK experts, this is the first introduction to the just-released 2014 version. It will help students and developers alike master the basic concepts for building systems with

Software is pervasive in our lives. We are accustomed to dealing with the failures of much of that software - restarting an application is a very familiar solution. Such solutions are unacceptable when the software controls our cars, airplanes and medical devices or manages our private information. These applications must run without error. SPARK provides a means, based on mathematical proof, to guarantee that a program has no errors. SPARK is a formally defined programming language and a set of verification tools specifically designed to support the development of software used in high integrity applications. Using SPARK, developers can formally verify properties of their code such as information flow, freedom from runtime errors, functional correctness, security properties and safety properties. Written by two SPARK experts, this is the first introduction to the just-released 2014 version. It will help students and developers alike master the basic concepts for building systems with

Cay Horstmann's 8th edition of Java Concepts provides an approachable introduction to fundamental programming techniques and design skills, helping students master basic concepts and become competent

Get a quick introduction to the technologies, tools, and techniques for programming Virtual Reality on the latest generation of desktop and mobile VR hardware. With this hands-on guide, you’ll learn e

Cay Horstmann's 6th edition of Big Java, Early Objects provides a comprehensive and approachable introduction to fundamental programming techniques and design skills, and helps stu

Cay Horstmann's 8th edition of Java Concepts provides an approachable introduction to fundamental programming techniques and design skills, helping students mas

This book provides an introduction to the core features of the Python programming language and Matplotlib plotting routings for scientists and engineers (or students of either discipline) who want to

Based on a starter course for beginning graduate students, Core Statistics provides concise coverage of the fundamentals of inference for parametric statistical models, including both theory and practical numerical computation. The book considers both frequentist maximum likelihood and Bayesian stochastic simulation while focusing on general methods applicable to a wide range of models and emphasizing the common questions addressed by the two approaches. This compact package serves as a lively introduction to the theory and tools that a beginning graduate student needs in order to make the transition to serious statistical analysis: inference; modeling; computation, including some numerics; and the R language. Aimed also at any quantitative scientist who uses statistical methods, this book will deepen readers' understanding of why and when methods work and explain how to develop suitable methods for non-standard situations, such as in ecology, big data and genomics.

Based on a starter course for beginning graduate students, Core Statistics provides concise coverage of the fundamentals of inference for parametric statistical models, including both theory and practical numerical computation. The book considers both frequentist maximum likelihood and Bayesian stochastic simulation while focusing on general methods applicable to a wide range of models and emphasizing the common questions addressed by the two approaches. This compact package serves as a lively introduction to the theory and tools that a beginning graduate student needs in order to make the transition to serious statistical analysis: inference; modeling; computation, including some numerics; and the R language. Aimed also at any quantitative scientist who uses statistical methods, this book will deepen readers' understanding of why and when methods work and explain how to develop suitable methods for non-standard situations, such as in ecology, big data and genomics.

Focusing strictly on teaching free-format RPG programming methods, this book will help programmers wishing to upgrade their skillsThis how-to guide offers a concise and thorough introduction to the in

Introduction and Advancement in C++ Programming Absolute C++ is a comprehensive introduction to the C++ programming language. The text is organized arou

An introduction to the life and achievements of the founder of Tesla Motors describes his early achievements in computer programming, his creation of a tech empire, his electric cars designs and his a

Python is the most popular programming language for beginners because it's fun, powerful, and easy to learn. So why should your introductory Python book be long and tedious? Python Crash Course gets y

Essential C# programming skills—made easy! C# 5.0: A Beginner's Guide provides a hands-on, easy-to-follow introduction to object-oriented programming with C#. The book presents 150+ examples with uncl

Provides a comprehensive coverage of both the deterministic and stochastic models of life contingencies, risk theory, credibility theory, multi-state models, and an introduction to modern mathematical

This text covers fundamentals used in the navigation and guidance of modern aerospace vehicles, in both atmospheric and space flight. It can be used as a textbook supporting a graduate level course on aerospace navigation and guidance, a guide for self-study, or a resource for practicing engineers and researchers. It begins with an introduction that discusses why navigation and guidance ought to be considered together and delineates the class of systems of interest in navigation and guidance. The book then presents the necessary fundamentals in deterministic and stochastic systems theory and applies them to navigation. Next, the book treats optimization and optimal control for application in optimal guidance. In the final chapter, the book introduces problems where two competing controls exercise authority over a system, leading to differential games. Fundamentals of Aerospace Navigation and Guidance features examples illustrating concepts and homework problems at the end of all chapte

"This timely new text provides an accessible introduction to teaching Computing, and computer programming. Specifically designed for non-specialists who need to develop new skills in Computing in orde

"This timely new text provides an accessible introduction to teaching Computing, and computer programming. Specifically designed for non-specialists who need to develop new skills in Computing in orde

Presents an introduction to computer programming for kids. This book takes kids' step-by-step through the basics of computer programming and how to work with code, the language of the future.

This complete book for Java newcomers wanting to learn Android programming is divided into two parts: Introduction to Java and Android Application Development. The first section discusses the three to

Striking a balance between theory and practice, this graduate-level text is perfect for students in the applied sciences. The author provides a clear introduction to the classical methods, how they work and why they sometimes fail. Crucially, he also demonstrates how these simple and classical techniques can be combined to address difficult problems. Many worked examples and sample programs are provided to help the reader make practical use of the subject material. Further mathematical background, if required, is summarized in an appendix. Topics covered include classical methods for linear systems, eigenvalues, interpolation and integration, ODEs and data fitting, and also more modern ideas like adaptivity and stochastic differential equations.

A solid introduction to mathematical modeling for a range of chemical engineering applications, covering model formulation, simplification and validation. It explains how to describe a physical/chemical reality in mathematical language and how to select the type and degree of sophistication for a model. Model reduction and approximation methods are presented, including dimensional analysis, time constant analysis and asymptotic methods. An overview of solution methods for typical classes of models is given. As final steps in model building, parameter estimation and model validation and assessment are discussed. The reader is given hands-on experience of formulating new models, reducing the models and validating the models. The authors assume the knowledge of basic chemical engineering, in particular transport phenomena, as well as basic mathematics, statistics and programming. The accompanying problems, tutorials, and projects include model formulation at different levels, analysis, pa

Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery.

This self-contained introduction shows how stochastic geometry techniques can be used for studying the behaviour of heterogeneous cellular networks (HCNs). The unified treatment of analytic results and approaches, collected for the first time in a single volume, includes the mathematical tools and techniques used to derive them. A single canonical problem formulation encompassing the analytic derivation of Signal to Interference plus Noise Ratio (SINR) distribution in the most widely-used deployment scenarios is presented, together with applications to systems based on the 3GPP-LTE standard, and with implications of these analyses on the design of HCNs. An outline of the different releases of the LTE standard and the features relevant to HCNs is also provided. A valuable reference for industry practitioners looking to improve the speed and efficiency of their network design and optimization workflow, and for graduate students and researchers seeking tractable analytical results for per

Separation logic is the twenty-first-century variant of Hoare logic that permits verification of pointer-manipulating programs. This book covers practical and theoretical aspects of separation logic at a level accessible to beginning graduate students interested in software verification. On the practical side it offers an introduction to verification in Hoare and separation logics, simple case studies for toy languages, and the Verifiable C program logic for the C programming language. On the theoretical side it presents separation algebras as models of separation logics; step-indexed models of higher-order logical features for higher-order programs; indirection theory for constructing step-indexed separation algebras; tree-shares as models for shared ownership; and the semantic construction (and soundness proof) of Verifiable C. In addition, the book covers several aspects of the CompCert verified C compiler, and its connection to foundationally verified software analysis tools. All c

Originating from the authors' own graduate course at the University of North Carolina, this material has been thoroughly tried and tested over many years, making the book perfect for a two-term course or for self-study. It provides a concise introduction that covers all of the measure theory and probability most useful for statisticians, including Lebesgue integration, limit theorems in probability, martingales, and some theory of stochastic processes. Readers can test their understanding of the material through the 300 exercises provided. The book is especially useful for graduate students in statistics and related fields of application (biostatistics, econometrics, finance, meteorology, machine learning, and so on) who want to shore up their mathematical foundation. The authors establish common ground for students of varied interests which will serve as a firm 'take-off point' for them as they specialize in areas that exploit mathematical machinery.

Campesato presents this guide to using HTML5 for mobile programming, giving instruction with a mix of prose and code. A general introduction to the intersection of HTML5 and mobile is followed by spec

Complexity science is the study of systems with many interdependent components. Such systems - and the self-organization and emergent phenomena they manifest - lie at the heart of many challenges of global importance. This book is a coherent introduction to the mathematical methods used to understand complexity, with plenty of examples and real-world applications. It starts with the crucial concepts of self-organization and emergence, then tackles complexity in dynamical systems using differential equations and chaos theory. Several classes of models of interacting particle systems are studied with techniques from stochastic analysis, followed by a treatment of the statistical mechanics of complex systems. Further topics include numerical analysis of PDEs, and applications of stochastic methods in economics and finance. The book concludes with introductions to space-time phases and selfish routing. The exposition is suitable for researchers, practitioners and students in complexity sci

Lévy processes are rich mathematical objects and constitute perhaps the most basic class of stochastic processes with a continuous time parameter. This book is intended to provide the reader with comprehensive basic knowledge of Lévy processes, and at the same time serve as an introduction to stochastic processes in general. No specialist knowledge is assumed and proofs are given in detail. Systematic study is made of stable and semi-stable processes, and the author gives special emphasis to the correspondence between Lévy processes and infinitely divisible distributions. All serious students of random phenomena will find that this book has much to offer. Now in paperback, this corrected edition contains a brand new supplement discussing relevant developments in the area since the book's initial publication.

The technology of mechanized program verification can play a supporting role in manykinds of research projects in computer science, and related tools for formal proof-checking areseeing increasing ado

Written for computer programming students, hobbyists, and professionals, FUNDAMENTALS OF PYTHON: DATA STRUCTURES is an introduction to object-oriented design and data structures using the popular Pyth

"Featuring an introduction to stochastic calculus, this book uniquely blends diffusion equations and random walk theory and provides an interdisciplinary approach by including numerous practical examp

A Complete, Hands-on Guide to Programmable Logic ControllersProgrammable Logic Controllers: Industrial Control offers a thorough introduction to PLC programming with focus on real-world industrial pro

A friendly and accessible introduction to the most useful algorithmsComputer algorithms are the basic recipes for programming. Professional programmers need to know how to use algorithms to solve di

Nominal sets provide a promising new mathematical analysis of names in formal languages based upon symmetry, with many applications to the syntax and semantics of programming language constructs that involve binding, or localising names. Part I provides an introduction to the basic theory of nominal sets. In Part II, the author surveys some of the applications that have developed in programming language semantics (both operational and denotational), functional programming and logic programming. As the first book to give a detailed account of the theory of nominal sets, it will be welcomed by researchers and graduate students in theoretical computer science.

A practical introduction for using iOS 6 to create universal appsIf you have prior experience programming in an object-oriented language and are eager to start building universal apps for iPad and iPh

Cay Horstmann s seventh edition of Java Concepts provides an approachable introduction to fundamental programming techniques and design skills, helping students master basic concepts and become compet

This text is an unbound, binder-ready edition. Python for Everyone, 1st Edition is a comprehensive introduction to Python and computer programming, which focuses on the principles of programming, soft