Root mean square

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Zayed, G., T. Ismail, and Y. Fahmy, "Visible Light Communications Localization Error Enhancement using Parameter Relaxation", 2020 16th International Computer Engineering Conference (ICENCO): IEEE Xplore, pp. 191 - 196, 2020. Abstractvisible-light-communications-localization-error-enhancement-using-parameter-relaxation.pdf
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In this paper, we propose applying a parameter relaxation technique to the location estimation algorithm that is based on the Received Signal Strength (RSS) of Visible Light Communications (VLC). A hybrid system of localization balancing is introduced, where the localization algorithm is developed with and without this efficient parameter relaxation. The results show that applying the parameter relaxation reduces the localization Root Mean Square (RMS) error by 43% of that without relaxation; and the processing time is reduced by 18% of that without relaxation. Moreover, the parameter relaxation approach is compared with previous work that is based on Artificial Neural Networks (ANN), where the performance of the proposed relaxation technique is shown to be over 4 times better than that of the ANN-based approach.