DocumentCode :
1875995
Title :
Application of Fuzzy Closeness and Probabilistic Neural Network in Multi-Sensor Fusion
Author :
Xu, Xiaoguang ; Shen, Hongda ; Ling, Youzhu ; Shen, Lina
Author_Institution :
Electr. Eng. Coll., Anhui Polytech. Univ., Wuhu, China
fYear :
2010
fDate :
10-12 Dec. 2010
Firstpage :
1
Lastpage :
5
Abstract :
The method of fuzzy closeness was used to calculate the closeness between the detected value in multi-sensor detecting system and the real value and convert it to weight of the sensor more close to the real value, which can help get the measured value. Probabilistic neural network can classify the detecting degree with values measured by many kinds of sensors, and the target category can be obtained precisely and quickly. The application of both fuzzy closeness and probabilistic neural network has fast convergence rate and high precise. So the judgment can be made precisely and quickly in multi-sensor fusion system.
Keywords :
fuzzy neural nets; sensor fusion; fuzzy closeness; multisensor detection; multisensor fusion; probabilistic neural network; Artificial neural networks; Classification algorithms; Data models; Engines; Fires; Probabilistic logic; Temperature sensors;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5391-7
Electronic_ISBN :
978-1-4244-5392-4
Type :
conf
DOI :
10.1109/CISE.2010.5676999
Filename :
5676999
Link To Document :
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