TY - GEN
T1 - Ancillary techniques for neural network applications
AU - El-Sharkawi, M. A.
AU - Huang, S. J.
PY - 1994
Y1 - 1994
N2 - To a large extent, the successful implementation of neural nets depends on several ancillary techniques for data preprocessing, training and testing. Some of these techniques are investigated and discussed in this paper. They include genetic algorithm, fuzzy logic theory, query-based learning and feature extraction. For each technique, the paradigm, theory and application are described. The advantages of the application of these ancillary techniques for the neural networks are also listed. The simulation results for each proposed technique showed their significant role and practicality.
AB - To a large extent, the successful implementation of neural nets depends on several ancillary techniques for data preprocessing, training and testing. Some of these techniques are investigated and discussed in this paper. They include genetic algorithm, fuzzy logic theory, query-based learning and feature extraction. For each technique, the paradigm, theory and application are described. The advantages of the application of these ancillary techniques for the neural networks are also listed. The simulation results for each proposed technique showed their significant role and practicality.
UR - http://www.scopus.com/inward/record.url?scp=0028727428&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0028727428&partnerID=8YFLogxK
U2 - 10.1109/icnn.1994.374802
DO - 10.1109/icnn.1994.374802
M3 - Conference contribution
AN - SCOPUS:0028727428
SN - 078031901X
T3 - IEEE International Conference on Neural Networks - Conference Proceedings
SP - 3724
EP - 3729
BT - IEEE International Conference on Neural Networks - Conference Proceedings
PB - IEEE
T2 - Proceedings of the 1994 IEEE International Conference on Neural Networks. Part 1 (of 7)
Y2 - 27 June 1994 through 29 June 1994
ER -