Non-linear Transformations in Wiener Space of the Form Y(t)

Non-linear Transformations in Wiener Space of the Form Y(t) PDF Author: John Edward Hafstrom
Publisher:
ISBN:
Category : Transformations (Mathematics)
Languages : en
Pages : 180

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Book Description

Non-linear Transformations in Wiener Space of the Form Y(t)

Non-linear Transformations in Wiener Space of the Form Y(t) PDF Author: John Edward Hafstrom
Publisher:
ISBN:
Category : Transformations (Mathematics)
Languages : en
Pages : 180

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Book Description


Stochastic Partial Differential Equations

Stochastic Partial Differential Equations PDF Author: Alison Etheridge
Publisher: Cambridge University Press
ISBN: 9780521483193
Category : Mathematics
Languages : en
Pages : 356

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Book Description
Consists of papers given at the ICMS meeting held in 1994 on this topic, and brings together some of the world's best known authorities on stochastic partial differential equations.

Applied Stochastic Differential Equations

Applied Stochastic Differential Equations PDF Author: Simo Särkkä
Publisher: Cambridge University Press
ISBN: 1316510085
Category : Business & Economics
Languages : en
Pages : 327

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Book Description
With this hands-on introduction readers will learn what SDEs are all about and how they should use them in practice.

Bilinear Stochastic Models and Related Problems of Nonlinear Time Series Analysis

Bilinear Stochastic Models and Related Problems of Nonlinear Time Series Analysis PDF Author: György Terdik
Publisher: Springer Science & Business Media
ISBN: 1461215528
Category : Mathematics
Languages : en
Pages : 275

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Book Description
The object of the present work is a systematic statistical analysis of bilinear processes in the frequency domain. The first two chapters are devoted to the basic theory of nonlinear functions of stationary Gaussian processes, Hermite polynomials, cumulants and higher order spectra, multiple Wiener-Itô integrals and finally chaotic Wiener-Itô spectral representation of subordinated processes. There are two chapters for general nonlinear time series problems.

From Geometry to Quantum Mechanics

From Geometry to Quantum Mechanics PDF Author: Yoshiaki Maeda
Publisher: Springer Science & Business Media
ISBN: 0817645306
Category : Mathematics
Languages : en
Pages : 326

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Book Description
* Invited articles in differential geometry and mathematical physics in honor of Hideki Omori * Focus on recent trends and future directions in symplectic and Poisson geometry, global analysis, Lie group theory, quantizations and noncommutative geometry, as well as applications of PDEs and variational methods to geometry * Will appeal to graduate students in mathematics and quantum mechanics; also a reference

Optimization by Vector Space Methods

Optimization by Vector Space Methods PDF Author: David G. Luenberger
Publisher: John Wiley & Sons
ISBN: 9780471181170
Category : Technology & Engineering
Languages : en
Pages : 348

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Book Description
Engineers must make decisions regarding the distribution of expensive resources in a manner that will be economically beneficial. This problem can be realistically formulated and logically analyzed with optimization theory. This book shows engineers how to use optimization theory to solve complex problems. Unifies the large field of optimization with a few geometric principles. Covers functional analysis with a minimum of mathematics. Contains problems that relate to the applications in the book.

Encyclopedia of Statistical Sciences, Volume 1

Encyclopedia of Statistical Sciences, Volume 1 PDF Author:
Publisher: John Wiley & Sons
ISBN: 0471743917
Category : Mathematics
Languages : en
Pages : 722

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Book Description
ENCYCLOPEDIA OF STATISTICAL SCIENCES

Nonlinear Markov Processes and Kinetic Equations

Nonlinear Markov Processes and Kinetic Equations PDF Author: Vassili N. Kolokoltsov
Publisher: Cambridge University Press
ISBN: 1139489739
Category : Mathematics
Languages : en
Pages : 394

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Book Description
A nonlinear Markov evolution is a dynamical system generated by a measure-valued ordinary differential equation with the specific feature of preserving positivity. This feature distinguishes it from general vector-valued differential equations and yields a natural link with probability, both in interpreting results and in the tools of analysis. This brilliant book, the first devoted to the area, develops this interplay between probability and analysis. After systematically presenting both analytic and probabilistic techniques, the author uses probability to obtain deeper insight into nonlinear dynamics, and analysis to tackle difficult problems in the description of random and chaotic behavior. The book addresses the most fundamental questions in the theory of nonlinear Markov processes: existence, uniqueness, constructions, approximation schemes, regularity, law of large numbers and probabilistic interpretations. Its careful exposition makes the book accessible to researchers and graduate students in stochastic and functional analysis with applications to mathematical physics and systems biology.

High-Dimensional Probability

High-Dimensional Probability PDF Author: Roman Vershynin
Publisher: Cambridge University Press
ISBN: 1108415199
Category : Business & Economics
Languages : en
Pages : 299

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Book Description
An integrated package of powerful probabilistic tools and key applications in modern mathematical data science.

Nonlinear Time Series Analysis

Nonlinear Time Series Analysis PDF Author: Ruey S. Tsay
Publisher: John Wiley & Sons
ISBN: 1119264065
Category : Mathematics
Languages : en
Pages : 516

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Book Description
A comprehensive resource that draws a balance between theory and applications of nonlinear time series analysis Nonlinear Time Series Analysis offers an important guide to both parametric and nonparametric methods, nonlinear state-space models, and Bayesian as well as classical approaches to nonlinear time series analysis. The authors—noted experts in the field—explore the advantages and limitations of the nonlinear models and methods and review the improvements upon linear time series models. The need for this book is based on the recent developments in nonlinear time series analysis, statistical learning, dynamic systems and advanced computational methods. Parametric and nonparametric methods and nonlinear and non-Gaussian state space models provide a much wider range of tools for time series analysis. In addition, advances in computing and data collection have made available large data sets and high-frequency data. These new data make it not only feasible, but also necessary to take into consideration the nonlinearity embedded in most real-world time series. This vital guide: • Offers research developed by leading scholars of time series analysis • Presents R commands making it possible to reproduce all the analyses included in the text • Contains real-world examples throughout the book • Recommends exercises to test understanding of material presented • Includes an instructor solutions manual and companion website Written for students, researchers, and practitioners who are interested in exploring nonlinearity in time series, Nonlinear Time Series Analysis offers a comprehensive text that explores the advantages and limitations of the nonlinear models and methods and demonstrates the improvements upon linear time series models.