Citation: Kt. Chong et Ag. Parlos, COMPARISON OF TRADITIONAL AND NEURAL-NETWORK APPROACHES TO STOCHASTICNONLINEAR-SYSTEM IDENTIFICATION, KSME International Journal, 11(3), 1997, pp. 267-278
Citation: Ha. Toliyat et al., A METHOD FOR DYNAMIC SIMULATION OF AIR-GAP ECCENTRICITY IN INDUCTION MACHINES, IEEE transactions on industry applications, 32(4), 1996, pp. 910-918
Citation: A. Atiya et Ag. Parlos, IDENTIFICATION OF NONLINEAR DYNAMICS USING A GENERAL SPATIOTEMPORAL NETWORK, Mathematical and computer modelling, 21(1-2), 1995, pp. 53-71
Authors:
PARLOS AG
FERNANDEZ B
ATIYA AF
MUTHUSAMI J
TSAI WK
Citation: Ag. Parlos et al., AN ACCELERATED LEARNING ALGORITHM FOR MULTILAYER PERCEPTRON NETWORKS, IEEE transactions on neural networks, 5(3), 1994, pp. 493-497
Citation: Ag. Parlos et al., APPLICATION OF THE RECURRENT MULTILAYER PERCEPTRON IN MODELING COMPLEX PROCESS DYNAMICS, IEEE transactions on neural networks, 5(2), 1994, pp. 255-266
Citation: Ag. Parlos et Jd. Metzger, FEASIBILITY STUDY OF A CONTAINED PULSED NUCLEAR PROPULSION ENGINE, Journal of propulsion and power, 10(2), 1994, pp. 269-278
Citation: Ag. Parlos et al., INCIPIENT FAULT-DETECTION AND IDENTIFICATION IN-PROCESS SYSTEMS USINGACCELERATED NEURAL-NETWORK LEARNING, Nuclear technology, 105(2), 1994, pp. 145-161
Citation: Ag. Parlos et al., EMPIRICAL-MODEL DEVELOPMENT AND VALIDATION WITH DYNAMIC LEARNING IN THE RECURRENT MULTILAYER PERCEPTRON, Nuclear technology, 105(2), 1994, pp. 271-290