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CAEPIA
2003
Springer
14 years 23 days 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
ETT
2002
142views Education» more  ETT 2002»
13 years 7 months ago
Adaptive state- dependent importance sampling simulation of markovian queueing networks
In this paper, a method is presented for the efficient estimation of rare-event (buffer overflow) probabilities in queueing networks using importance sampling. Unlike previously pr...
Pieter-Tjerk de Boer, Victor F. Nicola
IOR
2006
163views more  IOR 2006»
13 years 7 months ago
Adaptive Importance Sampling Technique for Markov Chains Using Stochastic Approximation
For a discrete-time finite-state Markov chain, we develop an adaptive importance sampling scheme to estimate the expected total cost before hitting a set of terminal states. This s...
T. P. I. Ahamed, Vivek S. Borkar, S. Juneja
ICIAP
2007
ACM
14 years 7 months ago
An information theoretic rule for sample size adaptation in particle filtering
To become robust, a tracking algorithm must be able to support uncertainty and ambiguity often inherently present in the data in form of occlusion and clutter. This comes usually ...
Oswald Lanz
CSE
2009
IEEE
14 years 2 months ago
Self-Tuning the Parameter of Adaptive Non-linear Sampling Method for Flow Statistics
—Flow statistics is a basic task of passive measurement and has been widely used to characterize the state of the network. Adaptive Non-Linear Sampling (ANLS)is one of the most a...
Chengchen Hu, Bin Liu