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» Smoothed Particle Filtering for Dynamic Bayesian Networks
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2010
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13 years 2 months ago
Efficient Particle Filtering via Sparse Kernel Density Estimation
Particle filters (PFs) are Bayesian filters capable of modeling nonlinear, non-Gaussian, and nonstationary dynamical systems. Recent research in PFs has investigated ways to approp...
Amit Banerjee, Philippe Burlina
ICASSP
2008
IEEE
14 years 2 months ago
A new Particle Filtering algorithm with structurally optimal importance function
Bayesian estimation in nonlinear stochastic dynamical systems has been addressed for a long time. Among other solutions, Particle Filtering (PF) algorithms propagate in time a Mon...
Boujemaa Ait-El-Fquih, François Desbouvries
ADHOCNOW
2005
Springer
14 years 1 months ago
Location Tracking in Mobile Ad Hoc Networks Using Particle Filters
Mobile ad hoc networks (MANET) are dynamic networks formed on-the-fly as mobile nodes move in and out of each others’ transmission ranges. In general, the mobile ad hoc networki...
Rui Huang, Gergely V. Záruba
HYBRID
2003
Springer
14 years 25 days ago
Estimation of Distributed Hybrid Systems Using Particle Filtering Methods
Abstract. Networked embedded systems are composed of a large number of components that interact with the physical world via a set of sensors and actuators, have their own computati...
Xenofon D. Koutsoukos, James Kurien, Feng Zhao
TCSV
2010
13 years 2 months ago
Object Tracking in Structured Environments for Video Surveillance Applications
Abstract--We present a novel tracking method for effectively tracking objects in structured environments. The tracking method finds applications in security surveillance, traffic m...
Junda Zhu, Yuanwei Lao, Yuan F. Zheng