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Optimisation of particle filters using simultaneous perturbation stochastic approximation

Abstract:
This paper addresses the optimisation of particle filtering methods aka Sequential Monte Carlo (SMC) methods using stochastic approximation. First, the SMC algorithm is parameterised smoothly by a parameter. Second, optimisation of an average cost function is performed using Simultaneous Perturbation Stochastic Approximation (SPSA). Simulations demonstrate the efficiency of our algorithm.
Publication status:
Published

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Institution:
University of Oxford
Division:
MPLS
Department:
Statistics
Role:
Author
Journal:
2003 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOL VI, PROCEEDINGS More from this journal
Volume:
6
Pages:
681-684
Publication date:
2003-01-01
ISSN:
1520-6149
Language:
English
Pubs id:
pubs:190644
UUID:
uuid:f6caad3f-5879-492d-a93a-838aa1c78dfa
Local pid:
pubs:190644
Source identifiers:
190644
Deposit date:
2012-12-19

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