Large deviations for discrete-time processes with averaging O. V. Gulinsky and A. Yu. Veretennikov.. This item is unavailable.
Language: English
Published by Utrecht, VSP, 1993
- Hardcover
- Used
Seller: Antiquariat Bookfarm, Löbnitz, GermanyAntiquariat Bookfarm
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Ex-library with stamp and library-signature. GOOD condition, some traces of use. Ancien Exemplaire de bibliothèque avec signature et cachet. BON état, quelques traces d'usure. Ehem. Bibliotheksexemplar mit Signatur und Stempel. GUTER Zustand, ein paar Gebrauchsspuren. 60 GUL 9789067641487 Sprache: Englisch Gewicht in Gramm: 550.
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- Title
- Large deviations for discrete-time processes with averaging O. V. Gulinsky and A. Yu. Veretennikov.
- Publisher
- Utrecht, VSP
- Publication year
- 1993
- Condition
- Gut
- Binding
- Hardcover
- Language
- English
- ISBN 10
- 9067641480
- ISBN 13
- 9789067641487
- Item weight
- 550 grams
- Seller catalogs
- SA MATHEMATIK
01/07 This title is now available from Walter de Gruyter. Please see www.degruyter.com for more information. This book is mainly based on the Cramér--Chernoff renowned theorem, which deals with the 'rough' logarithmic asymptotics of the distribution of sums of independent, identically distributed random variables. The authors approach primarily the extensions of this theory to dependent, and in particular, nonmarkovian cases on function spaces. Recurrent algorithms of identification and adaptive control form the main examples behind the large deviation problems in this volume. The first part of the book exploits some ideas and concepts of the martingale approach, especially the concept of the stochastic exponential. The second part of the book covers Freindlin's approach, based on the Frobenius-type theorems for positive operators, which prove to be effective for the cases in consideration.
"Synopsis" may belong to another edition of this title.
Synopsis
Based on the Cramer-Chernoff theorem, which deals with the "rough" logarithmic asymptotics of the distribution of sums of independent, identically random variables, this work primarily approaches the extensions of this theory to dependent and, in particular, non-Markovian cases on function spaces. Recurrent algorithms of identification and adaptive control form the main examples behind the large deviation problems in this volume. The first part of the book exploits some ideas and concepts of the martingale approach, especially the concept of the stochastic exponential. The second part covers Freidlin's approach, based on the Frobenius-type theorems for positive operators, whuch prove to be effective for the cases in consideration. The book should be of value and interest to scientists in the field of probability, statistics and electrical engineering, as well as physicists dealing with statistical mechanics.
"About the title" may belong to another edition of this title.