title: Second order neurons and learning in Cohen-Grossberg networks.
abstract: The well known Cohen-Grossberg network is modified to include second order neural interconnections and also to have a learning component. Sufficient conditions are obtained for the existence of a globally exponentially stable equilibrium. The model provides a two-fold generalization of the Cohen-Grossberg network in the sense if one removes the learning component, then one gets a network with second order synaptic interactions; if both the learning component and the second order interactions are removed, then the model reduces to the standard Cohen-Grossberg network.
authors.affiliation: School of Informatics and Engineering, Flinders University, G.P.O. Box 2100, Adelaide, Australia. gopal@infoeng.flinders.edu.au
authors.forename: K
authors.initials: K
authors.lastname: Gopalsamy
mesh_terms: D007858:Learning; D008433:Mathematics; D016571:Neural Networks, Computer; D009474:Neurons / Q000166:cytology / Q000378:metabolism