Title :
Evaluation of neural networks for automatic target recognition
Author :
Przytula, K. Wojtek ; Thompson, Don
Author_Institution :
Hughes Res. Labs., Malibu, CA, USA
Abstract :
In automatic target recognition we often face a problem in having to train a large neural network upon a very limited data set. This paper presents methods designed to analyze trained networks. The methods allow us to investigate how the network makes its decisions as well as its generalization properties. The methods interact with each other and are intended to be used as a complete set. They use techniques of sensitivity analysis, linear algebra, and rule extraction. They have been coded in Matlab as a toolbox and tested on a large number of real networks
Keywords :
covariance matrices; feature extraction; generalisation (artificial intelligence); learning (artificial intelligence); linear algebra; neural nets; object recognition; radar computing; radar target recognition; sensitivity analysis; target tracking; Matlab toolbox; automatic target recognition; covariance matrix; generalization properties; limited data set; linear algebra; neural networks; rule extraction; sensitivity analysis; trained networks analysis; Design methodology; Electronic mail; Infrared sensors; Laboratories; Linear algebra; Mathematics; Neural networks; Sensitivity analysis; Target recognition; Testing;
Conference_Titel :
Aerospace Conference, 1997. Proceedings., IEEE
Conference_Location :
Snowmass at Aspen, CO
Print_ISBN :
0-7803-3741-7
DOI :
10.1109/AERO.1997.574896
