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- W2172297533 abstract "In networked systems, state estimation is hampered by communication limits. Past approaches, which consider scheduling sensors through deterministic event-triggers, reduce communication and maintain estimation quality. However, these approaches destroy the Gaussian property of the state, making it computationally intractable to obtain an exact minimum mean squared error estimate. We propose a stochastic event-triggered sensor schedule for state estimation which preserves the Gaussianity of the system, extending previous results from the single-sensor to the multi-sensor case." @default.
- W2172297533 created "2016-06-24" @default.
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- W2172297533 date "2015-02-10" @default.
- W2172297533 modified "2023-10-01" @default.
- W2172297533 title "Multi-Sensor Scheduling for State Estimation with Event-Based, Stochastic Triggers" @default.
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- W2172297533 doi "https://doi.org/10.48550/arxiv.1502.03068" @default.
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