Energy-based event-triggered state estimation for hidden Markov models

DOI10.1016/j.automatica.2017.02.012zbMath1371.93191OpenAlexW2593873482MaRDI QIDQ2409355

Dawei Shi, Tongwen Chen, Jiarao Huang

Publication date: 11 October 2017

Published in: Automatica (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.automatica.2017.02.012

zbMATH Keywords

hidden Markov modelsevent-triggered state estimationreference measure approachenergy harvesting sensors

Mathematics Subject Classification ID

Estimation and detection in stochastic control theory (93E10) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Discrete event control/observation systems (93C65)

Related Items (8)

Event-triggered sliding mode control of discrete-time two-dimensional systems in Roesser model ⋮ Event-triggered learning ⋮ Asynchronous observer‐based sliding mode control for 2‐D Markov jump Roesser systems ⋮ Robust event-triggered state estimation: a risk-sensitive approach ⋮ Event-triggered state estimation for Markovian jumping impulsive neural networks with interval time-varying delays ⋮ Learning hidden Markov models for linear Gaussian systems with applications to event-based state estimation ⋮ Event-triggered minimax state estimation with a relative entropy constraint ⋮ Event-triggered recursive state estimation for dynamical networks under randomly switching topologies and multiple missing measurements

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• Kalman Filtering With Intermittent Observations
• Event Based State Estimation With Time Synchronous Updates
• Event-Based Sensor Data Scheduling: Trade-Off Between Communication Rate and Estimation Quality
• Event triggered robust filter design for discrete‐time systems

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