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Springer Linear Stochastic Systems: Geometric Modeling & Estimation

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Description

Linear Stochastic Systems presents a comprehensive treatment of second-order stationary processes with applications across engineering and applied sciences. Building on foundational work from Kolmogorov, Wiener, and Cramer dating back to the 1940s, this volume explores the theory and practical modeling of stationary random signals and systems. The book addresses key problems in filtering, estimation, and identification of stochastic processes, combining classical results with modern refinements developed over decades of research. Ideal for engineers, mathematicians, and researchers working with signal processing, control systems, and statistical analysis of time series data.

Key Features

Covers second-order stationary processes with rigorous mathematical foundations established by Kolmogorov and Wiener.

Addresses filtering and modelling of stationary random signals essential for engineering applications.

Presents geometric approaches to stochastic systems estimation and identification problems.

Published by Springer as part of the Series in Contemporary Mathematics collection.

Synthesizes classical theory with modern developments in linear stochastic system analysis.

Product Specifications

Format
hardcover
Domain
Amazon UK
Release Date
11 May 2015
Listed Since
05 November 2014

Barcode

No barcode data available

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