CUED Publications database

Adaptive sequential Monte Carlo approach for real-time applications

Chau, TCP and Luk, W and Cheung, PYK and Eele, A and Maciejowski, J (2012) Adaptive sequential Monte Carlo approach for real-time applications. Proceedings - 22nd International Conference on Field Programmable Logic and Applications, FPL 2012. pp. 527-530.

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Abstract

This paper presents an adaptive Sequential Monte Carlo approach for real-time applications. Sequential Monte Carlo method is employed to estimate the states of dynamic systems using weighted particles. The proposed approach reduces the run-time computation complexity by adapting the size of the particle set. Multiple processing elements on FPGAs are dynamically allocated for improved energy efficiency without violating real-time constraints. A robot localisation application is developed based on the proposed approach. Compared to a non-adaptive implementation, the dynamic energy consumption is reduced by up to 70% without affecting the quality of solutions. © 2012 IEEE.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Control
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 12:16
Last Modified: 08 Dec 2014 02:21
DOI: 10.1109/FPL.2012.6339271