DocumentCode
289900
Title
Introduction of neural networks in the decentralized detection problems
Author
Duflos, E. ; Boyer, M.-P. ; Coquard, Y. ; Vanheeghe, P.
Author_Institution
Dept. Signaux et Syst., Inst. Superieur d´´Electron. du Nord, Lille, France
fYear
1993
fDate
17-20 Oct 1993
Firstpage
650
Abstract
The problem of decentralized detection appears when various sensors are used simultaneously to collect observations from multiple points apart from each other. In this case, some difficulties such as transmission errors, very high transmission rates or memory requirement may occur when a centralized detection is used. To override these limitations detection structures involving two processing levels have been introduced: the decentralized detection. Unfortunately the solutions proposed to the decentralized problem require many calculations. Basing their approach on the similarity between detection problems and neural networks the authors propose a neural approach to solve the decentralized detection problem with fewer calculations
Keywords
neural nets; sensor fusion; decentralized detection problems; memory requirement; neural networks; transmission errors; two-level processing; very high transmission rates; Backpropagation algorithms; Conference proceedings; Cybernetics; Equations; Explosions; Filters; Intelligent networks; Neural networks; Sensor fusion; White noise;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man and Cybernetics, 1993. 'Systems Engineering in the Service of Humans', Conference Proceedings., International Conference on
Conference_Location
Le Touquet
Print_ISBN
0-7803-0911-1
Type
conf
DOI
10.1109/ICSMC.1993.385090
Filename
385090
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