Gaussian Random Processes

This book PDF is perfect for those who love Mathematics genre, written by I.A. Ibragimov and published by Springer Science & Business Media which was released on 06 December 2012 with total hardcover pages 285. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Gaussian Random Processes books below.

Gaussian Random Processes
Author : I.A. Ibragimov
File Size : 42,8 Mb
Publisher : Springer Science & Business Media
Language : English
Release Date : 06 December 2012
ISBN : 9781461262756
Pages : 285 pages
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Gaussian Random Processes by I.A. Ibragimov Book PDF Summary

The book deals mainly with three problems involving Gaussian stationary processes. The first problem consists of clarifying the conditions for mutual absolute continuity (equivalence) of probability distributions of a "random process segment" and of finding effective formulas for densities of the equiva lent distributions. Our second problem is to describe the classes of spectral measures corresponding in some sense to regular stationary processes (in par ticular, satisfying the well-known "strong mixing condition") as well as to describe the subclasses associated with "mixing rate". The third problem involves estimation of an unknown mean value of a random process, this random process being stationary except for its mean, i. e. , it is the problem of "distinguishing a signal from stationary noise". Furthermore, we give here auxiliary information (on distributions in Hilbert spaces, properties of sam ple functions, theorems on functions of a complex variable, etc. ). Since 1958 many mathematicians have studied the problem of equivalence of various infinite-dimensional Gaussian distributions (detailed and sys tematic presentation of the basic results can be found, for instance, in [23]). In this book we have considered Gaussian stationary processes and arrived, we believe, at rather definite solutions. The second problem mentioned above is closely related with problems involving ergodic theory of Gaussian dynamic systems as well as prediction theory of stationary processes.

Gaussian Random Processes

The book deals mainly with three problems involving Gaussian stationary processes. The first problem consists of clarifying the conditions for mutual absolute continuity (equivalence) of probability distributions of a "random process segment" and of finding effective formulas for densities of the equiva lent distributions. Our second problem is to describe

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