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• W2477175076 abstract "In traditional time-based sampling, the sampling mechanism is triggered by predetermined sampling times, which are mostly uniformly spaced (i.e., periodic). Alternatively, in event-based sampling, some predefined events on the signal to be sampled trigger the sampling mechanism; that is, sampling times are determined by the signal and the event space. Such an alternative mechanism, setting the sampling times free, can enable simple (e.g., binary) representations in the event space. In real-time applications, the induced sampling times can be easily traced and reported with high accuracy, whereas the amplitude of a time-triggered sample needs high data rates for high accuracy. In this chapter, for some statistical signal processing problems, namely detection (i.e., binary hypothesis testing) and parameter estimation, in resource-constrained distributed systems (e.g., wireless sensor networks), we show how to make use of the time dimension for data/information fusion, which is not possible through the traditional fixed-time sampling." @default.
• W2477175076 created "2016-08-23" @default.
• W2477175076 creator A5036320427 @default.
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• W2477175076 creator A5056360019 @default.
• W2477175076 creator A5077692655 @default.
• W2477175076 date "2018-09-03" @default.
• W2477175076 modified "2023-10-03" @default.
• W2477175076 title "Event-Based Control and Signal Processing" @default.
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• W2477175076 doi "https://doi.org/10.1201/b19013" @default.
• W2477175076 hasPublicationYear "2018" @default.
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