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.Full text not available from this repository.
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.
|Divisions:||Div F > Control|
|Depositing User:||Cron Job|
|Date Deposited:||09 Dec 2016 17:24|
|Last Modified:||29 Mar 2017 03:28|