Model Identification for Wireless Sensor Networks | IEEE Conference Publication | IEEE Xplore

Model Identification for Wireless Sensor Networks


Abstract:

In many lifetime enhancement strategies for wireless sensor networks (WSNs) it is often necessary to identify the statistical model of the underlying physical field. We c...Show More

Abstract:

In many lifetime enhancement strategies for wireless sensor networks (WSNs) it is often necessary to identify the statistical model of the underlying physical field. We consider the problem of in-situ inference as an exemplary application and propose an in-situ model estimation algorithm that works in tandem with a parametric distributed filtering procedure. We demonstrate, via averaged-gradient analysis and simulations, that the resulting adaptive filter is stable, robust and, importantly, fully scalable. It compares favorably with kernel-regression inference, and typically significantly outperforms the latter when the spatio-temporal variations in the natural field are relatively rapid.
Date of Conference: 26-30 November 2007
Date Added to IEEE Xplore: 26 December 2007
ISBN Information:
Print ISSN: 1930-529X
Conference Location: Washington, DC, USA

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