| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 411177 | Neurocomputing | 2007 | 8 Pages |
Abstract
Time delay neural networks trained with the backpropagation algorithm are derived for the gun fire control system to correct the miss distance between a target and the projectiles from the gun. Its performance is compared to optimum linear filter based on minimum mean square error [R.E. Kalman, A new approach to linear filtering and prediction problems, J. Basic Eng. 82D (1960) 35–44.]. The structure of the proposed neural controller is described and performance results are shown.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Yang Weon Lee,