DocumentCode :
233619
Title :
Indoor location algorithm of back propagation Neural Network based on residual analysis
Author :
Chen Cheng ; Wang Ping ; Xing Jianchun
Author_Institution :
Coll. of Nat. Defense, PLA Univ. of Sci. & Technol., Nanjing, China
fYear :
2014
fDate :
28-30 July 2014
Firstpage :
467
Lastpage :
471
Abstract :
In indoor environment, there are gross errors in random measured values of base station, which has effect on generalization ability of BP neural network and then results in low location accuracy. In order to improve location accuracy, location algorithm of BP Neural Network based on residual analysis is proposed, namely conducting pretreatment on measured values separately in training phase and location phase of BP neural network with twice residual analysis and getting rid of measured value with bigger error. The simulation result shows that such algorithm is better than BP algorithm both in aspects of convergence rate and location effect.
Keywords :
backpropagation; indoor radio; mobile computing; neural nets; telecommunication computing; back propagation neural network; base station random measured values; convergence rate; generalization ability; gross errors; indoor environment; indoor location algorithm; location accuracyimprovement; location effect; location phase; residual analysis; training phase; Accuracy; Algorithm design and analysis; Convergence; Estimation; Measurement uncertainty; Neural networks; Training; BP neural network; Indoor location; Residual analysis;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2014 33rd Chinese
Conference_Location :
Nanjing
Type :
conf
DOI :
10.1109/ChiCC.2014.6896668
Filename :
6896668
Link To Document :
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