Savran, M. Erkan2016-01-082016-01-081991http://hdl.handle.net/11693/17364Ankara : 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.viii, 40 leavesEnglishinfo:eu-repo/semantics/openAccessHopfield neural networkContent addressable memoryFixedpoint programmingCellular neural networksQA76.87 .S28 1991Neural networks (Computer science).Machine theory.Thesis