Estimation for discrete-time systems with multiple packet dropouts using covariance information
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Publication:409893
DOI10.1016/j.mcm.2011.05.036zbMath1235.94032OpenAlexW2047267564WikidataQ59552204 ScholiaQ59552204MaRDI QIDQ409893
Aurora Hermoso-Carazo, Josefa Linares-Pérez, María Jesús García-Ligero
Publication date: 15 April 2012
Published in: Mathematical and Computer Modelling (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.mcm.2011.05.036
Non-Markovian processes: estimation (62M09) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Sampling theory in information and communication theory (94A20)
Related Items (3)
Optimal filtering for networked systems with stochastic sensor gain degradation ⋮ Estimation from a multisensor environment for systems with multiple packet dropouts and correlated measurement noises ⋮ Least-squares estimators for systems with stochastic sensor gain degradation, correlated measurement noises and delays in transmission modelled by Markov chains
Cites Work
- Optimal linear estimation for systems with multiple packet dropouts
- Filtering of images corrupted by multiplicative and white plus coloured additive noises using covariance information
- Design of a fixed-interval smoother using covariance information based on the innovations approach in linear discrete-time stochastic systems
- Recursive fixed-point smoothing algorithm from covariances based on uncertain observations with correlation in the uncertainty
- Optimal \(\mathcal H_{\infty}\) filtering in networked control systems with multiple packet dropouts
- Optimal filtering with random sensor delay, multiple packet dropout and uncertain observations
- Optimal Full-Order and Reduced-Order Estimators for Discrete-Time Systems With Multiple Packet Dropouts
- Kalman Filtering With Intermittent Observations
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