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Active Queue Management (AQM) methods attempt to predict and control network router queue levels and provide feedback regarding network congestion to data sources through packet marking/dropping. AQM methods have not employed statistical signal processing principles largely due to the requirement of low complexity. In this paper, we apply optimal ltering and target tracking methods to the design of AQM. In particular, we develop Kalman Filter based AQM which results in router queues withdoi:10.1109/icassp.2009.4960194 dblp:conf/icassp/CotterM09 fatcat:vt76cbs6xjhrtbms37m2cmajq4