Synchronous-Asynchronous Simulated Kalman Filter Algorithm with Random Switching


Ibrahim, Zuwairie and Ab. Aziz, Nor Azlina and Mubin, Marizan and Mokhtar, Norrima (2020) Synchronous-Asynchronous Simulated Kalman Filter Algorithm with Random Switching. In: International Conference on Communication, Electrical and Computer Networks (ICCECN 2020), 25-26 Jan 2020, University of Malaya, Kuala Lumpur, Malaysia.

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The original Simulated Kalman Filter (SKF) is an optimizer that employs synchronous update mechanism. The agents in SKF update their solutions after all fitness calculations, prediction process, and measurement process are completed. An alternative to synchronous update is asynchronous update. In asynchronous update, only one agent does fitness calculation, prediction, measurement, and estimation processes at one time. A recent study shows that the asynchronous SKF outperforms synchronous SKF. In this study, synchronous and asynchronous mechanisms are combined in SKF. At first, the SKF starts with synchronous update. If no improved solution is found, the SKF changes its update mechanism. The decision to switch from synchronous to asynchronous or vice versa is made randomly. Using the CEC2014 benchmark test suite, experimental results indicate that the proposed synchronous-asynchronous SKF with random switching outperforms the asynchronous SKF including the synchronous SKF as well.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Kalman filtering, Simulated Kalman Filter, Synchronous, Asynchronous
Subjects: Q Science > Q Science (General)
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Rosnani Abd Wahab
Date Deposited: 10 Sep 2021 13:59
Last Modified: 21 Dec 2022 06:20


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