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CAEPIA
2003
Springer
14 years 1 months ago
A Method to Adaptively Propagate the Set of Samples Used by Particle Filters
Abstract. In recent years, particle filters have emerged as a useful tool that enables the application of Bayesian reasoning to problems requiring dynamic state estimation. The ef...
Alvaro Soto
ICASSP
2010
IEEE
13 years 8 months ago
Particle filter adaptation for distributed sensors via set membership
A distributed set-membership-constrained particle filter (SMCPF) is developed for decentralized tracking applications using wireless sensor networks. Unlike existing PF alternati...
Shahrokh Farahmand, Stergios I. Roumeliotis, Georg...
GECCO
2004
Springer
106views Optimization» more  GECCO 2004»
14 years 2 months ago
The Kalman Swarm: A New Approach to Particle Motion in Swarm Optimization
Abstract. Particle Swarm Optimization is gaining momentum as a simple and effective optimization technique. We present a new approach to PSO that significantly reduces the number...
Christopher K. Monson, Kevin D. Seppi
GECCO
2005
Springer
190views Optimization» more  GECCO 2005»
14 years 2 months ago
An efficient evolutionary algorithm applied to the design of two-dimensional IIR filters
This paper presents an efficient technique of designing twodimensional IIR digital filters using a new algorithm involving the tightly coupled synergism of particle swarm optimiza...
Swagatam Das, Amit Konar, Uday Kumar Chakraborty
CVPR
2003
IEEE
14 years 10 months ago
Variational Inference for Visual Tracking
The likelihood models used in probabilistic visual tracking applications are often complex non-linear and/or nonGaussian functions, leading to analytically intractable inference. ...
Jaco Vermaak, Neil D. Lawrence, Patrick Pér...