Event-based statistical signal processing

Yasin Yilmaz, George V. Moustakides, Xiaodong Wang, Alfred O. Hero

Research output: Chapter in Book/Report/Conference proceedingChapter

6 Scopus citations

Abstract

In traditional time-based sampling, the sampling mechanism is triggered by predetermined sampling times, which aremostly 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.

Original languageEnglish (US)
Title of host publicationEvent-Based Control and Signal Processing
PublisherCRC Press
Pages457-485
Number of pages29
ISBN (Electronic)9781482256567
ISBN (Print)9781482256550
DOIs
StatePublished - Jan 1 2015
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Computer Science(all)

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