Sensor placement for optimal estimation of vector-valued diffusion processes

DOI10.1016/j.sysconle.2018.09.004zbMath1408.93128OpenAlexW2895364251MaRDI QIDQ1729054

Mohamed-Ali Belabbas, Xudong Chen

Publication date: 27 February 2019

Published in: Systems \& Control Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.sysconle.2018.09.004

zbMATH Keywords

estimationWiener processsensor design

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Estimation and detection in stochastic control theory (93E10)

Cites Work

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• Sensor selection for Kalman filtering of linear dynamical systems: complexity, limitations and greedy algorithms
• Optimal experiment design in a filtering context with application to sampled network data
• A trace inequality of John von Neumann
• Optimal actuator/sensor location for active noise regulator and tracking control problems
• Optimal Designs for Steady-State Kalman Filters
• Energy futures prices: term structure models with Kalman filter estimation
• Introduction to Stochastic Models in Biology
• Econometric Analysis of Realized Volatility and its Use in Estimating Stochastic Volatility Models
• Linear-Quadratic Optimal Actuator Location
• Geometric methods for optimal sensor design
• Linear Stochastic Systems
• Doubly Stochastic Matrices and the Diagonal of a Rotation Matrix
• Stochastic differential equations. An introduction with applications.

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