gaussian random processes von ibragimov i a (11 Ergebnisse)

Zustand: Very Good. 277 pp., Hardcover, previous owner's name to the front free endpaper, spine faded, else very good. - If you are reading this, this item is actually (physically) in our stock and ready for shipment once ordered. We are not bookjackers. Buyer is responsible for any additional duties, taxes, or fees required by recipient's country.

X/275 S./pp., Originalpappband (publisher's cardboard covers), Bibliotheksexemplar in gutem Zustand / exlibrary in good condition (Stempel auf Titel / title stamped, Rückenschildchen / lettering pannel to the spine, Block sehr gut / contents fine, keine Unterstreichungen oder Anstreichungen / no underlining or remarks, in Folie eingeschlagen / wrapped up in foil), (Applications of Mathematics 9), Sprache: englisch.

gebundene Ausgabe. Zustand: Gut. 275 Seiten Der Erhaltungszustand des hier angebotenen Werks ist trotz seiner Bibliotheksnutzung sehr sauber. Es befindet sich neben dem Rückenschild lediglich ein Bibliotheksstempel im Buch; ordnungsgemäß entwidmet. In ENGLISCHER Sprache. Sprache: Englisch Gewicht in Gramm: 650.

Zustand: New. In.

Zustand: Gut. 1. Edition;. Gr.8° Orig.-Pappband; 650g; [Englisch]; Rücken ausgeblichen, sonst kaum Gebrauchsspuren // spine faded, otherwise fine 1. Edition; [lgr=L] _ x2x_. BUCH.

Taschenbuch. Zustand: Neu. Gaussian Random Processes | I. A. Ibragimov (u. a.) | Taschenbuch | x | Englisch | 2011 | Springer | EAN 9781461262770 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.

Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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.

Zustand: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher.

Zustand: New. In.

Zustand: New. 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.

Buch. Zustand: Neu. Neuware - 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.