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Springer Estimators for Uncertain Dynamic Systems - Mathematics Applications

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Description

Estimators for Uncertain Dynamic Systems is a comprehensive academic resource addressing the critical challenge of state estimation in dynamic processes across aerospace, naval engineering, energetics, economics, and biology. This volume explores how to construct effective estimators that recover essential information about system state from measurement data when inherent uncertainties and measurement noise are present. The work formulates variational problems designed to solve estimation challenges in an optimal manner, providing theoretical foundations and practical methodologies for engineers and researchers working with complex, unpredictable systems. Part of Springer's Mathematics and Its Applications series (volume 458), this text offers rigorous mathematical treatments suitable for graduate-level study and professional application in control design, system modelling, and dynamic process analysis.

Key Features

Springer publication providing peer-reviewed content on estimation theory for uncertain dynamic systems and processes.

Covers application domains including aerospace engineering, naval engineering, energetics, economics, and biological systems.

Addresses optimal estimation through variational problem formulation for systems with measurement noise and uncertainty.

Part of the Mathematics and Its Applications series volume 458, positioning it within established academic literature.

Product Specifications

Format
paperback
Domain
Amazon UK
Publication Date
06 October 2012
Listed Since
07 November 2013

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