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Item Details
Title: LINEAR STOCHASTIC SYSTEMS
A GEOMETRIC APPROACH TO MODELING, ESTIMATION AND IDENTIFICATION
By: Anders Lindquist, Giorgio Picci
Format: Paperback

List price: £139.99
Our price: £118.99
Discount:
15% off
You save: £21.00
ISBN 10: 3662526182
ISBN 13: 9783662526187
Availability: Usually dispatched within 1-3 weeks.
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Publisher: SPRINGER-VERLAG BERLIN AND HEIDELBERG GMBH & CO. KG
Pub. date: 29 October, 2016
Edition: Softcover reprint of the original 1st ed. 2015
Series: Series in Contemporary Mathematics 1
Pages: 781
Description: This book presents a treatise on the theory and modeling of second-order stationary processes, including an exposition on selected application areas that are important in the engineering and applied sciences.
Synopsis: This book presents a treatise on the theory and modeling of second-order stationary processes, including an exposition on selected application areas that are important in the engineering and applied sciences. The foundational issues regarding stationary processes dealt with in the beginning of the book have a long history, starting in the 1940s with the work of Kolmogorov, Wiener, Cramer and his students, in particular Wold, and have since been refined and complemented by many others. Problems concerning the filtering and modeling of stationary random signals and systems have also been addressed and studied, fostered by the advent of modern digital computers, since the fundamental work of R.E. Kalman in the early 1960s. The book offers a unified and logically consistent view of the subject based on simple ideas from Hilbert space geometry and coordinate-free thinking. In this framework, the concepts of stochastic state space and state space modeling, based on the notion of the conditional independence of past and future flows of the relevant signals, are revealed to be fundamentally unifying ideas. The book, based on over 30 years of original research, represents a valuable contribution that will inform the fields of stochastic modeling, estimation, system identification, and time series analysis for decades to come. It also provides the mathematical tools needed to grasp and analyze the structures of algorithms in stochastic systems theory.
Illustrations: 37 Illustrations, black and white; XV, 781 p. 37 illus.
Publication: Germany
Imprint: Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Returns: Returnable
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