Analysis of the Performance of Decentralized Sensor Network with Correlated Observations


Show simple item record Gnanapandithan, N. Natarajan, Bala 2010-08-10T14:14:49Z 2010-08-10T14:14:49Z 2010-08-10T14:14:49Z
dc.description.abstract In this paper, we study the performance of a decentralized sensor network in the presence of correlated additive Gaussian noise. We propose a parallel genetic algorithm approach to simultaneously optimize both the fusion rule and the local decision rules in the sense of minimizing the probability of error. Our results show that the algorithm converges to a majority-like fusion rule irrespective of the degree of correlation and that the local decision rules play a key role in determining the performance of the overall system in the case of correlated observations. We also show that the performance of the system degrades with increase in the correlation between the observations. en_US
dc.publisher Institute of Electrical and Electronics Engineers en_US
dc.relation.uri en_US
dc.rights Copyright 2007 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. en_US
dc.subject Gaussian noise en_US
dc.subject Correlation theory en_US
dc.subject Decision theory en_US
dc.subject Genetic algorithms en_US
dc.subject Parallel algorithms en_US
dc.subject Performance evaluation en_US
dc.title Analysis of the Performance of Decentralized Sensor Network with Correlated Observations en_US
dc.type Conference paper en_US 2007 en_US
dc.citation.ctitle 2007 2nd International Symposium on Wireless Pervasive Computing en_US
dc.citation.doi doi:10.1109/ISWPC.2007.342678 en_US
dc.citation.epage 626 en_US
dc.citation.issn 1-4244-0523-8 en_US
dc.citation.spage 622 en_US
dc.description.conference 2007 2nd International Symposium on Wireless Pervasive Computing. February 5-7, 2007. San Juan, Puerto Rico. en_US
dc.contributor.authoreid bala en_US

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