stochastic approximation dynamical systems viewpoint von borkar vivek (9 Ergebnisse)

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Zustand: New. Simple, compact toolkit for designing and analyzing algorithms, with concrete examples from control and communications engineering, artificial intelligence, economic modelling. Num Pages: 176 pages. BIC Classification: PBT; PBWL. Category: (UP) Postgraduate, Research & Scholarly. Dimension: 161 x 235 x 16. Weight in Grams: 386. . 2008. 1st Edition. hardcover. . . . . Books ship from the US and Ireland.

Hardcover. Zustand: Brand New. 1st edition. 164 pages. 9.25x6.00x0.50 inches. In Stock.

Taschenbuch. Zustand: Neu. Stochastic Approximation: A Dynamical Systems Viewpoint | Vivek S. Borkar | Taschenbuch | Texts and Readings in Mathematics | xv | Englisch | 2025 | Springer | EAN 9789819982790 | 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 - This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.

Hardcover. Zustand: Brand New. 2nd edition. 288 pages. 9.25x6.10x0.71 inches. In Stock.

Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book serves as an advanced text for a graduate course on stochastic algorithms for the students of probability and statistics, engineering, economics and machine learning. This second edition gives a comprehensive treatment of stochastic approximation algorithms based on the ordinary differential equation (ODE) approach which analyses the algorithm in terms of a limiting ODE. It has a streamlined treatment of the classical convergence analysis and includes several recent developments such as concentration bounds, avoidance of traps, stability tests, distributed and asynchronous schemes, multiple time scales, general noise models, etc., and a category-wise exposition of many important applications. It is also a useful reference for researchers and practitioners in the field.

Hindustan Book Agency, New Delhi 2008. ix, 164, (2) pp. Hardcover. Fine condition. (Text and Readings in Mathematics 48).