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This paper applies a Markov chain Monte Carlo-based (MCMC) particle filter on the multiple target tracking problem. Traditional particle filters employ the sequential importance sampling/resampling method along with the MCMC move step, which is commonly used as a means to improve diversity among particles. The MCMC-based particle filter applied in this(More)
This paper presents a comparative study of randomized algorithms for computation of a class of high dimensional Gaussian weighted integrals. The work is an extension of past research by Keister et al. and later by Papageorgiou et al. who used non-product (grid-less) multidimensional quadrature rules and Quasi Monte Carlo respectively for integration in up(More)
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