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- W2964302485 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.
- W2964302485 created "2019-07-30" @default.
- W2964302485 creator A5023990842 @default.
- W2964302485 date "2016-12-01" @default.
- W2964302485 modified "2023-09-27" @default.
- W2964302485 title "Predictive and self triggering for event-based state estimation" @default.
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- W2964302485 doi "https://doi.org/10.1109/cdc.2016.7798733" @default.
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