Gaussian Random Processes (Applications of Mathematics, Volume 9) von Ibragimov, I.A., and Y.A. Rozanov: UsedGood Hardcover (1978)

Beschreibung

Hardcover; translated by A.B. Aries; surplus library copy with the usual stampings and reference number affixed to the front; fading and shelf wear to exterior; bumps to the corners and the spine ends; otherwise in good condition with clean text and tight binding.

Bestandsnummer des Verk�ufers 76130

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Bibliografische Details

Titel: Gaussian Random Processes (Applications of Mathematics, Volume 9)
Verlag: Springer-Verlag
Ver�ffentlichungsdatum: 1978
Sprache: Englisch
ISBN-10: 038790302X
ISBN-13: 9780387903026
Bindung: Hardcover
Zustand: UsedGood

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Inhaltsangabe

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.

Rese�a del editor

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.

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