Savran, M. E.Morgül, Ö.2016-02-082016-02-0819941045-9227http://hdl.handle.net/11693/25993We consider the design problem for a class of discrete-time and continuous-time neural networks. We obtain a characterization of all connection weights that store a given set of vectors into the network; that is, each given vector becomes an equilibrium point of the network. We also give sufficient conditions that guarantee the asymptotic stability of these equilibrium points.EnglishConvergence of numerical methodsMathematical modelsNeural networksSystem stabilitySystems analysisVectorsAsymptotic stabilityContinuous time neural networksDiscrete time neural networksDynamic associative neural memoriesEquilibrium pointsAssociative storageArticle10.1109/72.286920