Title :
Employing CHNN to Develop a Data Refining Algorithm for Wireless Sensor Networks
Author :
Chen, Joy Iong-Zong ; Yu, Chieh Chung ; Hsieh, Meng Tsun ; Chung, Yi Nug
Author_Institution :
Dept. of Commun. Eng., Dayeh Univ., Changhua, Taiwan
fDate :
March 31 2009-April 2 2009
Abstract :
In this report a data refining algorithm (DFA) for obtaining the relationships between wireless sensor measurements and existing tracks is proposed. It is known that a DFA plays an important role in wireless sensors for target tracking over WSN (wireless sensor network) deployments. However, a new approach to data refining is here investigated, wherein the matching between mobile sensor measurements and existing target tracks can achieve global consideration. Embedded within the traditional HNN (Hopfield neural networks) is adopted. In this research, the network is guaranteed to converge into a stable state when performing a data association. The HNN-based DFA is combined with mobile sensors in a WSN system to demonstrate the target tracking capabilities. Finally, computer simulation results indicate that this approach successfully solves the data association problems addressed over WSN environments.
Keywords :
Hopfield neural nets; mobile radio; sensor fusion; target tracking; telecommunication computing; wireless sensor networks; CHNN; DFA algorithm; competitive Hopfield neural network; data association; data refining algorithm; mobile sensor measurement; target tracking; wireless sensor network; Computer science; Data engineering; Doped fiber amplifiers; Electronic mail; Hopfield neural networks; Sensor fusion; Sensor systems; Surveillance; Target tracking; Wireless sensor networks; CHNN (competitive Hopfield neural network); DFA (data fusion algorithm); WSN (wireless sensor network); mobile sensors;
Conference_Titel :
Computer Science and Information Engineering, 2009 WRI World Congress on
Conference_Location :
Los Angeles, CA
Print_ISBN :
978-0-7695-3507-4
DOI :
10.1109/CSIE.2009.666
