Title :
Analysis of feature extraction by inverse mapping and Alopex algorithm
Author :
Nagashino, Hirofumi ; Yamamoto, Hidenori ; Pandya, Abhijit S. ; Kinouchi, Yohsuke
Author_Institution :
Dept. of Electr. & Electron. Eng., Tokushima Univ., Japan
fDate :
27 Jun-2 Jul 1994
Abstract :
This paper describes two methods of analysis of feature extraction characteristics of pattern recognition neural networks and their application to a three-layer feedforward network that learns by backpropagation. One method is inverse mapping and the other is calculation by Alopex algorithm, which is an iterative and stochastic processing to minimize or maximize a cost function. By these methods the receptive fields of the units in the hidden and output layers are obtained. Effectiveness of these methods are demonstrated
Keywords :
backpropagation; feature extraction; feedforward neural nets; iterative methods; minimax techniques; stochastic processes; Alopex algorithm; backpropagation; cost function; feature extraction; inverse mapping; iterative method; neural networks; pattern recognition; stochastic processing; three-layer feedforward network; Backpropagation algorithms; Cost function; Feature extraction; Feedforward neural networks; Iterative algorithms; Iterative methods; Neural networks; Pattern analysis; Pattern recognition; Stochastic processes;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374596
