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» Speeeding Up Markov Chain Monte Carlo Algorithms
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88
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ICASSP
2008
IEEE
15 years 7 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
89
Voted
CORR
2008
Springer
107views Education» more  CORR 2008»
15 years 22 days ago
Estimating Signals with Finite Rate of Innovation from Noisy Samples: A Stochastic Algorithm
As an example of the recently introduced concept of rate of innovation, signals that are linear combinations of a finite number of Diracs per unit time can be acquired by linear fi...
Vincent Yan Fu Tan, Vivek K. Goyal
ICSNC
2007
IEEE
15 years 7 months ago
Movement Prediction Using Bayesian Learning for Neural Networks
Nowadays, path prediction is being extensively examined for use in the context of mobile and wireless computing towards more efficient network resource management schemes. Path pr...
Sherif Akoush, Ahmed Sameh
IPPS
2010
IEEE
14 years 10 months ago
On the parallelisation of MCMC-based image processing
Abstract--The increasing availability of multi-core and multiprocessor architectures provides new opportunities for improving the performance of many computer simulations. Markov C...
Jonathan M. R. Byrd, Stephen A. Jarvis, Abhir H. B...
ICMI
2005
Springer
215views Biometrics» more  ICMI 2005»
15 years 6 months ago
Multimodal multispeaker probabilistic tracking in meetings
Tracking speakers in multiparty conversations constitutes a fundamental task for automatic meeting analysis. In this paper, we present a probabilistic approach to jointly track th...
Daniel Gatica-Perez, Guillaume Lathoud, Jean-Marc ...