Markov random fields / Yu. A. Rozanov. Transl. by Constance M. Elson;

Rozanov, Jurij A. and Constance M. Elson:

ISBN 10: 3540907084 / ISBN 13: 9783540907084

Published by New York ; Heidelberg ; Berlin : Springer,, 1982

About this Item

IX, 201 S. ; 25 cm In English language. Hardbound with title to spine and cover (no dust jacket). Former library copy with external labelings removed from boards. Page edges slightly darkened, otherwise with clean text and well preserved. Signature stamps on endpapers and title. + + + Originalpappeinband mit Rücken- und Deckelbetitelung, ohne = kein Schutzumschlag. Ordentlich ausgesondertes Bibliotheksexemplar mit entfernten äußerlichen Kennzeichnungen. Einband tlls. leicht berieben oder beschabt, Schnitt dezent nachgedunkelt, sonst textsauber und gepflegt. Signatur- / Entwidmungsstempel a. Vorsatz und Titel. 3540907084 Werktäglicher Versand. Jede Lieferung m. ordentl. Rechnung und ausgew. MwSt. Der Versand erfolgt als Büchersendung / Einschreiben mit der Deutschen Post bzw. als Päckchen / Paket mit DHL. Die Lieferzeit ist abhängig von der Versandart und beträgt innerhalb Deutschlands 3-5 Tage, in der EU 5 - 12 Tage. KEIN Versand an Packstationen. Körperschaften und juristische Personen werden auf Wunsch per offener Rechnung beliefert. Sprache: Englisch Gewicht in Gramm: 550.

Seller Inventory # 43732

Bibliographic Details

• Title: Markov random fields / Yu. A. Rozanov. Transl. by Constance M. Elson
• Publisher: New York ; Heidelberg ; Berlin : Springer,
• Publication Date: 1982
• Language: English
• ISBN 10: 3540907084
• ISBN 13: 9783540907084
• Binding: Gebundene Ausgabe
• Edition: en, Literaturverz. S. 195 - 197.
• Condition: Gut

About this title

Synopsis

In this book we study Markov random functions of several variables. What is traditionally meant by the Markov property for a random process (a random function of one time variable) is connected to the concept of the phase state of the process and refers to the independence of the behavior of the process in the future from its behavior in the past, given knowledge of its state at the present moment. Extension to a generalized random process immediately raises nontrivial questions about the definition of a suitable" phase state," so that given the state, future behavior does not depend on past behavior. Attempts to translate the Markov property to random functions of multi-dimensional "time," where the role of "past" and "future" are taken by arbitrary complementary regions in an appro­ priate multi-dimensional time domain have, until comparatively recently, been carried out only in the framework of isolated examples. How the Markov property should be formulated for generalized random functions of several variables is the principal question in this book. We think that it has been substantially answered by recent results establishing the Markov property for a whole collection of different classes of random functions. These results are interesting for their applications as well as for the theory. In establishing them, we found it useful to introduce a general probability model which we have called a random field. In this book we investigate random fields on continuous time domains. Contents CHAPTER 1 General Facts About Probability Distributions §1.