Design and stability of Hopfield associative memory
Date
1991
Authors
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Advisor
Morgül, Ömer
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Language
English
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Abstract
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.
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Degree Discipline
Electrical and Electronic Engineering
Degree Level
Master's
Degree Name
MS (Master of Science)