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» Challenges for Data Mining in Distributed Sensor Networks
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132
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IPSN
2004
Springer
15 years 8 months ago
Estimation from lossy sensor data: jump linear modeling and Kalman filtering
Due to constraints in cost, power, and communication, losses often arise in large sensor networks. The sensor can be modeled as an output of a linear stochastic system with random...
Alyson K. Fletcher, Sundeep Rangan, Vivek K. Goyal
125
Voted
IJDMB
2008
105views more  IJDMB 2008»
15 years 2 months ago
Temporal representation for gene networks: towards a qualitative temporal data mining
: Recently lots of studies aim at modeling and inferring gene networks. Modeling tools propose graphical models having almost nothing about time description of events and regards t...
Nicolas Turenne, Sylviane R. Schwer
152
Voted
IPPS
2010
IEEE
15 years 17 days ago
Distributed monitoring of conditional entropy for anomaly detection in streams
In this work we consider the problem of monitoring information streams for anomalies in a scalable and efficient manner. We study the problem in the context of network streams wher...
Chrisil Arackaparambil, Sergey Bratus, Joshua Brod...
117
Voted
DMSN
2005
ACM
15 years 4 months ago
Timely data delivery in sensor networks using whirlpool
In this paper, we introduce a rotating interrogation technique for sensor networks called Whirlpool. Whirlpool provides opportunities to optimize data delivery in time-critical mo...
Divyasheel Sharma, Vladimir Zadorozhny, Panos K. C...
107
Voted
CDC
2008
IEEE
136views Control Systems» more  CDC 2008»
15 years 9 months ago
Distributed hypothesis testing with a fusion center: The conditionally dependent case
Abstract— The paper deals with decentralized Bayesian detection with M hypotheses, and N sensors making conditionally correlated measurements regarding these hypotheses. Each sen...
Kien C. Nguyen, Tansu Alpcan, Tamer Basar