The neuronet going is examined near the construction of nonlinear dynamic model of Gammershteyna. Research results confirmed efficiency of application of networks of radially-base type for the construction of nonlinear model of Gammershteyna. Application of generalized-regressive network even at tuning only of gravimetric parameters of network provides the receipt of acceptable results. Tuning of all of parameters of networks allows substantially to promote exactness of decision of task of authentication, considerably increasing teaching time here.
INS, model of Gammershteyna, radially-base network, design of process of authentication
“Postroenie modeli Gammershteina s pomoshchiu radialno-bazisnoi seti”,
Scientific Works of Kharkiv National Air Force University,