DocumentCode :
2892142
Title :
Polynomial neural networks for airborne applications
Author :
Krile, T. ; Rothstein, S. ; McAulay, A. ; Juang, B.
Author_Institution :
Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH, USA
fYear :
1989
fDate :
22-26 May 1989
Firstpage :
682
Abstract :
The authors have attempted to develop a polynomial neural network which will present a pilot with optimal maneuvers for missile evasion and to show the benefits of the network relative to a look-up table. They used an inductive, unsupervised learning model, which is well suited for dynamical systems and results in compact, computationally fast representations. An aircraft-missile computer simulation program is used to gather the data used in the neural network learning phase as well as in construction of the look-up table. The inputs to the neural model are variables such as aircraft velocity and initial range. Outputs are several maneuvers and associated maneuver times which provide the best chance for survival. Results show that a polynomial network can be generated that performs calculations approximating a simulator approximately a million times faster for the case of determining whether a aircraft needs to respond to a missile attack. Computer experiments suggest that for simple decision cases any of the three approaches are likely to be adequate: run a simulator in realtime, use a look-up table of precomputed runs, or use a polynomial network to approximate the simulator computations
Keywords :
aerospace computing; aerospace simulation; aircraft instrumentation; learning systems; military computing; missiles; neural nets; polynomials; aerospace computing; airborne applications; aircraft velocity; aircraft-missile computer simulation program; dynamical systems; inductive unsupervised learning model; initial range; missile evasion; optimal maneuvers; polynomial neural network; Aerospace electronics; Aircraft manufacture; Application software; Computer science; Computer simulation; Missiles; Neural networks; Polynomials; Supervised learning; Table lookup;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Aerospace and Electronics Conference, 1989. NAECON 1989., Proceedings of the IEEE 1989 National
Conference_Location :
Dayton, OH
Type :
conf
DOI :
10.1109/NAECON.1989.40284
Filename :
40284
Link To Document :
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