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- W4299910850 abstract "Event-based state estimation can achieve estimation quality comparable to traditional time-triggered methods, but with a significantly lower number of samples. In networked estimation problems, this reduction in sampling instants does, however, not necessarily translate into better usage of the shared communication resource. Because typical event-based approaches decide instantaneously whether communication is needed or not, free slots cannot be reallocated immediately, and hence remain unused. In this paper, novel predictive and self triggering protocols are proposed, which give the communication system time to adapt and reallocate freed resources. From a unified Bayesian decision framework, two schemes are developed: self-triggers that predict, at the current triggering instant, the next one; and predictive triggers that indicate, at every time step, whether communication will be needed at a given prediction horizon. The effectiveness of the proposed triggers in trading off estimation quality for communication reduction is compared in numerical simulations." @default.
- W4299910850 created "2022-10-03" @default.
- W4299910850 creator A5023990842 @default.
- W4299910850 date "2016-09-23" @default.
- W4299910850 modified "2023-10-14" @default.
- W4299910850 title "Predictive and Self Triggering for Event-based State Estimation" @default.
- W4299910850 doi "https://doi.org/10.48550/arxiv.1609.07534" @default.
- W4299910850 hasPublicationYear "2016" @default.
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