Neural networks: theory and applications

Abstract

Weightless neural tools - toward cognitive macrostructures, L. Aleksander an estimation theoretic basis for the design of sorting and classification network, R.W. Brockett a self organizing ARTMAP neural architecture for supervized learning and pattern recognition, G.A. Carpenter et al hybrid neural network architectures - equilibrium systems that pay attention, L.N. Cooper neural networks for internal representation of movements in primates and robots, R. Eckmiller et al recognition and segmentation of characters in handwriting with selective attention, K. Fukushima et al adaptive acquisition of language, A.L. Gorin et al what connectionist models learn - learning and representation in connectionist networks, S.J. Hanson and D.J. Burr early vision, focal attention and neural nets, B. Julesz toward hierarchical matched filtering, R. Hecht-Nielsen some variations on training of recurrent networks, G.M. Kuhn and N.P. Herzberg generalized perception networks with nonlinear discriminant functions, S.Y. Kung et al neural tree networks, A. Sankar and R. Mammone capabilities and training of feedforward nets, E.D. Sontag a fast learning algorithm for multilayer neural network based on projection methods, S.J. Yeh and H. Stark.