DocumentCode
390692
Title
Object orient data fusion algorithms and its neural network implementations
Author
Yaohong, Kang ; Xiaoqin, Wu ; Yingbing, Wei ; Mingrui, Chen
Author_Institution
Inst. of Inf. Sci. & Technol., Hainan Univ., Haiko, China
Volume
1
fYear
2002
fDate
28-31 Oct. 2002
Firstpage
655
Abstract
This paper discusses a way to identify and locate a target collection in a given area at discrete time with neural network theory. With the given model, a report database is set up and maintained to store relevant detecting reports. Then a double layer self-organizing neural network is built using neural network adaptive resonant theory (ART) to offer a neural network implementation for the algorithms.
Keywords
ART neural nets; database management systems; multilayer perceptrons; object-oriented programming; self-organising feature maps; sensor fusion; ART; adaptive resonant theory; data fusion; discrete time; double layer self-organizing neural network; object oriented algorithms; relevant detecting reports; report database; Adaptive systems; Databases; Information science; Large-scale systems; Monitoring; Neural networks; Parallel processing; Real time systems; Resonance; Sensor fusion;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '02. Proceedings. 2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering
Print_ISBN
0-7803-7490-8
Type
conf
DOI
10.1109/TENCON.2002.1181359
Filename
1181359
Link To Document