Ankara : The Department of Electrical and Electronics Engineering and Institute of Engineering and Sciences, Bilkent Univ., 1991.Thesis (Master's) -- Bilkent University, 1991.Includes bibliographical references leaves 38-40.This thesis is concerned with the selection of connection weights of Hopfield
neural network model so that the network functions as a content addressable
memory (CAM). We deal with both the discrete and the continuous-time versions
of the model using hard-limiter and sigmoid type nonlinearities in the
neuron outputs. The analysis can be employed if any other invertible nonlinearity
is used. The general characterization of connection weights for fixed-point
programming and a condition for asymptotic stability of these fixed points are
presented. The general form of connection weights is then inserted in the condition
to obtain a design rule. The characterization procedure is also employed
for discrete-time cellular neural networks.Savran, M ErkanM.S
