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Introduction to Probability Theory and Stochastic Processes, Chiasson John



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Автор: Chiasson John
Название:  Introduction to Probability Theory and Stochastic Processes
Издательство: Wiley
Классификация:
Математика
Прикладная математика
Механическая обработка и материаловедение

ISBN: 111838279X
ISBN-13(EAN): 9781118382790
ISBN: 1-118382-9-X
ISBN-13(EAN): 978-1-118382-9-0
Обложка/Формат: Hardback
Страницы: 984
Вес: 1.506 кг.
Дата издания: 17.05.2013
Серия: Mathematics
Язык: English
Иллюстрации: Black & white illustrations, figures
Размер: 168 x 243 x 52
Читательская аудитория: Professional & vocational
Ключевые слова: Mathematics,Mechanical engineering & materials
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This comprehensive textbook provides an introduction to statistical methods for graduate engineers offering thorough coverage of important probability-related topics to aid in product and system design, reliability engineering, quality control, and more.



Introduction to Stochastic Integration

Автор: Kuo
Название: Introduction to Stochastic Integration
ISBN: 0387287205 ISBN-13(EAN): 9780387287201
Издательство: Springer
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Цена: 5224 р.
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Описание: The theory of stochastic integration, also called the Ito calculus, has a large spectrum of applications in virtually every scientific area involving random functions, but it can be a very difficult subject for people without much mathematical background. The Ito calculus was originally motivated by the construction of Markov diffusion processes from infinitesimal generators. Previously, the construction of such processes required several steps, whereas Ito constructed these diffusion processes directly in a single step as the solutions of stochastic integral equations associated with the infinitesimal generators. Moreover, the properties of these diffusion processes can be derived from the stochastic integral equations and the Ito formula. This introductory textbook on stochastic integration provides a concise introduction to the Ito calculus, and covers the following topics:* Constructions of Brownian motion;* Stochastic integrals for Brownian motion and martingales;* The Ito formula;* Multiple Wiener-Ito integrals;* Stochastic differential equations;* Applications to finance, filtering theory, and electric circuits.The reader should have a background in advanced calculus and elementary probability theory, as well as a basic knowledge of measure theory and Hilbert spaces. Each chapter ends with a variety of exercises designed to help the reader further understand the material.Hui-Hsiung Kuo is the Nicholson Professor of Mathematics at Louisiana State University. He has delivered lectures on stochastic integration at Louisiana State University, Cheng Kung University, Meijo University, and University of Rome "Tor Vergata," among others. He is also the author of Gaussian Measures in Banach Spaces (Springer 1975), and White Noise Distribution Theory (CRC Press 1996), and a memoir of his childhood growing up in Taiwan, An Arrow Shot into the Sun (Abridge Books 2004).

Elementary Probability Theory / With Stochastic Processes and an Introduction to Mathematical Finance

Автор: Chung K. L., AitSahlia Farid
Название: Elementary Probability Theory / With Stochastic Processes and an Introduction to Mathematical Finance
ISBN: 038795578X ISBN-13(EAN): 9780387955780
Издательство: Springer
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Цена: 7836 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Provides an introduction to probability theory and its applications.

Stochastic Processes

Автор: Gallager
Название: Stochastic Processes
ISBN: 1107039754 ISBN-13(EAN): 9781107039759
Издательство: Cambridge Academ
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Цена: 4831 р. 6901.00 -30%
Наличие на складе: Есть (1 шт.)
Описание: This definitive textbook provides a solid introduction to discrete and continuous stochastic processes, tackling a complex field in a way that instils a deep understanding of the relevant mathematical principles, and develops an intuitive grasp of the way these principles can be applied to modelling real-world systems. It includes a careful review of elementary probability and detailed coverage of Poisson, Gaussian and Markov processes with richly varied queuing applications. The theory and applications of inference, hypothesis testing, estimation, random walks, large deviations, martingales and investments are developed. Written by one of the world's leading information theorists, evolving over twenty years of graduate classroom teaching and enriched by over 300 exercises, this is an exceptional resource for anyone looking to develop their understanding of stochastic processes.

Stochastic processes

Автор: Parzen, Emanuel
Название: Stochastic processes
ISBN: 0898714419 ISBN-13(EAN): 9780898714418
Издательство: Eurospan
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Цена: 7874 р.
Наличие на складе: Нет в наличии.

Описание: This introductory textbook explains how and why probability models are applied to scientific fields such as medicine, biology, physics, oceanography, economics, and psychology to solve problems about stochastic processes. It does not just show how a problem is solved but explains why by formulating questions and first steps in the solutions.

Introduction To The Theory Of Random Processes (Graduate Studies In Mathematics)

Автор: Krylov
Название: Introduction To The Theory Of Random Processes (Graduate Studies In Mathematics)
ISBN: 0821829858 ISBN-13(EAN): 9780821829851
Издательство: Eurospan
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Цена: 4499 р.
Наличие на складе: Невозможна поставка.

Описание: Discusses the theory of stochastic processes. This book presents basics of discrete time martingales. It includes such topics as Wiener process, stationary processes, infinitely divisible processes, and Ito stochastic equations.

An Introduction to Stochastic Modeling,

Автор: Mark Pinsky
Название: An Introduction to Stochastic Modeling,
ISBN: 0123814162 ISBN-13(EAN): 9780123814166
Издательство: Elsevier Science
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Цена: 8250 р.
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Описание: Serving as the foundation for a one-semester course in stochastic processes for students familiar with elementary probability theory and calculus, Introduction to Stochastic Modeling, Fourth Edition, bridges the gap between basic probability and an intermediate level course in stochastic processes. The objectives of the text are to introduce students to the standard concepts and methods of stochastic modeling, to illustrate the rich diversity of applications of stochastic processes in the applied sciences, and to provide exercises in the application of simple stochastic analysis to realistic problems. New to this edition: . . Realistic applications from a variety of disciplines integrated throughout the text, including more biological applications. Plentiful, completely updated problems. Completely updated and reorganized end-of-chapter exercise sets, 250 exercises with answers. New chapters of stochastic differential equations and Brownian motion and related processes. Additional sections on Martingale and Poisson process

Introduction to Probability with Mathematica, Second Edition

Автор: Hastings
Название: Introduction to Probability with Mathematica, Second Edition
ISBN: 1420079387 ISBN-13(EAN): 9781420079388
Издательство: Taylor&Francis
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Цена: 9585 р.
Наличие на складе: Невозможна поставка.

Описание: Updated to conform to Mathematica® 7.0, this second edition shows how to easily create simulations from templates and solve problems using Mathematica. Along with new sections on order statistics, transformations of multivariate normal random variables, and Brownian motion, this edition offers an expanded section on Markov chains, more example data of the normal distribution, and more attention on conditional expectation. It also includes additional problems from Actuarial Exam P as well as new examples, exercises, and data sets. The accompanying CD-ROM contains updated Mathematica notebooks and a revised solutions manual is available for qualifying instructors.

Probability, Stochastic Processes, and Queueing Theory

Автор: Nelson
Название: Probability, Stochastic Processes, and Queueing Theory
ISBN: 0387944524 ISBN-13(EAN): 9780387944524
Издательство: Springer
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Цена: 10445 р.
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Описание: This detailed introduction to probability and stochastic processes shows how these subjects may be applied to computer performance modelling. Readers are assumed to be familiar with elementary linear algebra and calculus, including the concept of limit.

Introduction to Stochastic Processes with Applications to Bi

Автор: Allen Linda
Название: Introduction to Stochastic Processes with Applications to Bi
ISBN: 1439818827 ISBN-13(EAN): 9781439818824
Издательство: Taylor&Francis
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Цена: 6582 р.
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Описание: Delineates stochastic processes, emphasizing applications in biology. This book is organized according to the three types of stochastic processes: discrete time Markov chains, continuous time Markov chains and continuous time and state Markov processes. It contains a chapter on the biological applications of stochastic differential equations.

An Introduction to Continuous-Time Stochastic Processes

Автор: Capasso
Название: An Introduction to Continuous-Time Stochastic Processes
ISBN: 0817683453 ISBN-13(EAN): 9780817683450
Издательство: Springer
Цена: 9922 р.
Наличие на складе: Поставка под заказ.

Описание: Expanding on the first edition of An Introduction to Continuous-Time Stochastic Processes, this concisely written book is a rigorous and self-contained introduction to the theory of continuous-time stochastic processes. A balance of theory and applications, the work features concrete examples of modeling real-world problems from biology, medicine, industrial applications, finance, and insurance using stochastic methods. No previous knowledge of stochastic processes is required.

Introduction to Stationary Stochastic Processes

Автор: Lindgren
Название: Introduction to Stationary Stochastic Processes
ISBN: 1466586184 ISBN-13(EAN): 9781466586185
Издательство: Taylor&Francis
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Цена: 7622 р.
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Описание:

Stochastic processes are indispensable tools for development and research in signal and image processing, automatic control, oceanography, structural reliability, environmetrics, climatology, econometrics, and many other areas of science and engineering. Suitable for a one-semester course, Stationary Stochastic Processes for Scientists and Engineers teaches students how to use these processes efficiently. Carefully balancing mathematical rigor and ease of exposition, the book provides students with a sufficient understanding of the theory and a practical appreciation of how it is used in real-life situations. Special emphasis is on the interpretation of various statistical models and concepts as well as the types of questions statistical analysis can answer.

The text first introduces numerous examples from signal processing, economics, and general natural sciences and technology. It then covers the estimation of mean value and covariance functions, properties of stationary Poisson processes, Fourier analysis of the covariance function (spectral analysis), and the Gaussian distribution. The book also focuses on input-output relations in linear filters, describes discrete-time auto-regressive and moving average processes, and explains how to solve linear stochastic differential equations. It concludes with frequency analysis and estimation of spectral densities.

With a focus on model building and interpreting the statistical concepts, this classroom-tested book conveys a broad understanding of the mechanisms that generate stationary stochastic processes. By combining theory and applications, the text gives students a well-rounded introduction to these processes. To enable hands-on practice, MATLAB(R) code is available online.

An Introduction to Sparse Stochastic Processes

Автор: Unser
Название: An Introduction to Sparse Stochastic Processes
ISBN: 1107058546 ISBN-13(EAN): 9781107058545
Издательство: Cambridge Academ
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Цена: 3910 р.
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Описание: Providing a novel approach to sparsity, this comprehensive book presents the theory of stochastic processes that are ruled by linear stochastic differential equations, and that admit a parsimonious representation in a matched wavelet-like basis. Two key themes are the statistical property of infinite divisibility, which leads to two distinct types of behaviour - Gaussian and sparse - and the structural link between linear stochastic processes and spline functions, which is exploited to simplify the mathematical analysis. The core of the book is devoted to investigating sparse processes, including a complete description of their transform-domain statistics. The final part develops practical signal-processing algorithms that are based on these models, with special emphasis on biomedical image reconstruction. This is an ideal reference for graduate students and researchers with an interest in signal/image processing, compressed sensing, approximation theory, machine learning, or statistics.


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