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Robust Kalman Filtering for Signals and Systems With Large Uncertainties

cover the theory of robust state estimation for the case in which the process model contains significant uncertainties and non-linearities.;

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Robust Kalman Filtering for Signals and Systems with Large Uncertainties

of robust control theory. One of the major developments of modern control theory was the Kalman Filter and hence the development of a robust version;

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Kalman Filtering: With Real-Time Applications

on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering;

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Kalman Filtering: With Real-Time Applications

on innovation projection. Other topics include Kalman filtering for systems with correlated noise or colored noise, limiting Kalman filtering;

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Kalman Filtering and Information Fusion

filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced;

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Kalman Filtering and Information Fusion

filtering work well in the presence of various uncertainties and/or for multiple sensors/components. State-of-art techniques are introduced;

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Optimal Filtering

communication systems and digital filtering theory. Vital for students in the fields of control and communications, its contents are also relevant to;

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Kalman Filtering

textbook in advanced undergraduate and beginning graduate courses in stochastic processes and Kalman filtering. It is also appropriate for self;

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GPS-Based Optimal FIR Filtering of Clock Models

optimal FIR structures, which are inherently bounded input/bounded output (BIBO) stable and more robust against temporary uncertainties and round;

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Multi model Jumping Systems Robust Filtering and Fault Detection

-frequency robust filtering and higher order moment robust filtering schemes, as well as fault detection problems for multi-model jump systems, such;

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Nonlinear Filtering

techniques for nonlinear systems are discussed, including the extended, unscented and cubature Kalman filters. The cubature Kalman filter and its;

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Discrete Stochastic Processes and Optimal Filtering

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from;

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Discrete Stochastic Processes and Optimal Filtering

Optimal filtering applied to stationary and non-stationary signals provides the most efficient means of dealing with problems arising from;

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Kalman Filtering Techniques for Radar Tracking

for eliminating the real-time execution of complete recursive Kalman filtering matrix equations that reduce tracking and update time. It also;

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An Introduction to Kalman Filtering With Matlab Examples

state evolution and measurement processes are both linear and Gaussian. Given the ubiquity of such systems, the Kalman filter finds use in a;

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System Design and Control Integration for Advanced Manufacturing

. Little work considers model information for robust design particularly for the dynamic system. This book covers robust design for both static and;

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Optimal and Robust Estimation

today's high-performance systems. A Classic Revisited Optimal and Robust Estimation: With an Introduction to Stochastic Control Theory, Second;

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Kalman Filtering and Neural Networks

offers an introductory treatment of Kalman filters with an emphasis on basic Kalman filter theory, Rauch-Tung-Striebel smoother, and the extended;

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Approximate Kalman Filtering

Kalman filtering with emphasis on both its theoretical and practical aspects.;

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Signals and Systems Primer with MATLAB

Signals and Systems Primer with MATLAB (R) equally emphasizes the fundamentals of both analog and digital signals and systems. To ensure;

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Robust Control and Filtering for Time-Delay Systems

A discussion of robust control and filtering for time-delay systems. It provides information on approaches to stability, stabilization;

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Robust Control and Filtering for Time-Delay Systems

A discussion of robust control and filtering for time-delay systems. It provides information on approaches to stability, stabilization;

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Kalman Filtering

The purpose of the Kalman filter is to use measurements that are observed over time that contain noise (random variations) and other;

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Advanced Kalman Filtering, LeastSquares and Modeling

squares estimation or Kalman filtering that provide guidance on model structure and parameters, or make the estimator more robust to changes;

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Decentralized Control and Filtering in Interconnected Dynamical Systems

Based on the many approaches available for dealing with large-scale systems (LSS), Decentralized Control and Filtering in Interconnected;

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Nonlinear Kalman Filter for Multi-Sensor Navigation of Unmanned Aerial Vehicles

. The book focuses on Kalman filtering technics for UAV design, proposing a new design methodology and case study related to inertial navigation;

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Periodic Systems

robust stability; the problem of state estimation in its various forms, filtering, prediction and smoothing; control design methods, particularly;

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