Title :
Partial determination of particle motion using artificial neural networks
Author :
Chappell, S.K. ; Alouani, A.T. ; Rice, T.R. ; Gray, J.E.
Author_Institution :
Center for Manuf. & Technol. Utilization, Tennessee Technol. Univ., Cookeville, TN, USA
Abstract :
A technique that utilizes neural networks to provide information regarding the success or failure of a target/interceptor engagement is presented. This technique uses system identification, a Hopfield-network-based linear state estimator, and statistical decision theory. The approach is tested using simulated data. Preliminary simulation results are presented and discussed. Initial results indicate that this is a promising approach to the kill assessment problem
Keywords :
Hopfield neural nets; decision theory; military computing; state estimation; Hopfield-network; kill assessment problem; linear state estimator; military computing; neural networks; particle motion determination; statistical decision theory; system identification; target/interceptor engagement; Artificial neural networks; Doppler radar; Hopfield neural networks; Missiles; Propulsion; Pulp manufacturing; State estimation; System identification; Testing; Trajectory;
Conference_Titel :
Control Applications, 1992., First IEEE Conference on
Conference_Location :
Dayton, OH
Print_ISBN :
0-7803-0047-5
DOI :
10.1109/CCA.1992.269813
