Improved indoor localization based on received signal strength indicator and general regression neural network

10.18494/SAM.2019.2253

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Bibliographic Details
Main Authors:	Xu, S., Wang, Z., Zhang, H., Ge, S.S.
Other Authors:	ELECTRICAL AND COMPUTER ENGINEERING
Format:	Article
Published:	M Y U Scientific Publishing Division 2021
Subjects:	Filter General regression neural network (GRNN) Localization Maximum likelihood estimation (MLE) Received signal strength indicator (RSSI) ZigBee
Online Access:	https://scholarbank.nus.edu.sg/handle/10635/210047
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Institution:	National University of Singapore

id	sg-nus-scholar.10635-210047
record_format	dspace
spelling	sg-nus-scholar.10635-2100472024-04-16T10:49:20Z Improved indoor localization based on received signal strength indicator and general regression neural network Xu, S. Wang, Z. Zhang, H. Ge, S.S. ELECTRICAL AND COMPUTER ENGINEERING Filter General regression neural network (GRNN) Localization Maximum likelihood estimation (MLE) Received signal strength indicator (RSSI) ZigBee 10.18494/SAM.2019.2253 Sensors and Materials 31 6 2043-2060 2021-12-09T04:56:59Z 2021-12-09T04:56:59Z 2019 Article Xu, S., Wang, Z., Zhang, H., Ge, S.S. (2019). Improved indoor localization based on received signal strength indicator and general regression neural network. Sensors and Materials 31 (6) : 2043-2060. ScholarBank@NUS Repository. https://doi.org/10.18494/SAM.2019.2253 0914-4935 https://scholarbank.nus.edu.sg/handle/10635/210047 Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/ M Y U Scientific Publishing Division Scopus OA2019
institution	National University of Singapore
building	NUS Library
continent	Asia
country	Singapore Singapore
content_provider	NUS Library
collection	ScholarBank@NUS
topic	Filter General regression neural network (GRNN) Localization Maximum likelihood estimation (MLE) Received signal strength indicator (RSSI) ZigBee
spellingShingle	Filter General regression neural network (GRNN) Localization Maximum likelihood estimation (MLE) Received signal strength indicator (RSSI) ZigBee Xu, S. Wang, Z. Zhang, H. Ge, S.S. Improved indoor localization based on received signal strength indicator and general regression neural network
description	10.18494/SAM.2019.2253
author2	ELECTRICAL AND COMPUTER ENGINEERING
author_facet	ELECTRICAL AND COMPUTER ENGINEERING Xu, S. Wang, Z. Zhang, H. Ge, S.S.
format	Article
author	Xu, S. Wang, Z. Zhang, H. Ge, S.S.
author_sort	Xu, S.
title	Improved indoor localization based on received signal strength indicator and general regression neural network
title_short	Improved indoor localization based on received signal strength indicator and general regression neural network
title_full	Improved indoor localization based on received signal strength indicator and general regression neural network
title_fullStr	Improved indoor localization based on received signal strength indicator and general regression neural network
title_full_unstemmed	Improved indoor localization based on received signal strength indicator and general regression neural network
title_sort	improved indoor localization based on received signal strength indicator and general regression neural network
publisher	M Y U Scientific Publishing Division
publishDate	2021
url	https://scholarbank.nus.edu.sg/handle/10635/210047
_version_	1800915204368760832

Improved indoor localization based on received signal strength indicator and general regression neural network

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