Cai, Kai; Anderson, Brian; Yu, Changbin (Brad)
We study a new variant of consensus problems, termed 'local average consensus', in networks of agents. We consider the task of using sensor networks to perform distributed measurement of a parameter which has both spatial (in this paper ID) and temporal variations. Our idea is to maintain potentially useful local information regarding spatial variation, as contrasted with reaching a single, global consensus, as well as to mitigate the effect of measurement errors. We employ two schemes for...[Show more]
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