Title :
Applications and extensions of unsupervised BCM projection pursuit for time-dependent classification
Author :
Bachmann, Charles M. ; Luong, Dong Q. ; Moore, John W. ; Andreano, Keith J.
Author_Institution :
US Naval Res. Lab., Washington, DC, USA
Abstract :
Methods are developed for extending the unsupervised projection pursuit learning algorithm of Bienenstock, Cooper and Munro (BCM) (1982) to time-dependent classification problems. Recurrent and differential models of BCM which look for temporal structure in the evolution of high-dimensional inputs are described. Ordinary BCM obtains a 10db improvement in a noise tolerance study when compared with backward propagation (BP) for a database of simulated inverse synthetic aperature radar (ISAR) presentations. The recurrent and differential BCM models address the problem of classification from sequences of multiple presentations
Keywords :
neural nets; pattern classification; unsupervised learning; database; differential models; high-dimensional inputs; input evolution; multiple presentation models; noise tolerance; recurrent models; simulated inverse synthetic aperature radar; temporal structure; time-dependent classification; unsupervised projection pursuit learning algorithm; Additive noise; Airborne radar; Databases; Ear; Laboratories; Neural networks; Noise figure; Noise robustness; Pursuit algorithms; Signal to noise ratio;
Conference_Titel :
Neural Networks for Processing [1993] III. Proceedings of the 1993 IEEE-SP Workshop
Conference_Location :
Linthicum Heights, MD
Print_ISBN :
0-7803-0928-6
DOI :
10.1109/NNSP.1993.471873
