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The Dynamics of Learning in some Digital Networks

Fairhurst, Michael Christopher (1973) The Dynamics of Learning in some Digital Networks. Doctor of Philosophy (PhD) thesis, University of Kent. (doi:10.22024/UniKent/01.02.94337) (KAR id:94337)


This thesis is concerned with a study of learning in feedback networks of adaptive logic circuits. Random networks have been studied by various researchers, but previous work has not considered the adaptation mechanisms in dynamic logic networks which result from exposure to a non-random environment. Starting with a consideration of some limitations of a single-layer static network, the concept of a dynamic net (i.e. one with feedback connections) is introduced. The behaviour of the system is described in terms of its cycling activity in state space, and the effect of training on the state structure is considered. Subsequent experimental investigations consider unsupervised learning in the net where early evidence of a clustering effect is seen. This effect is found to be more pronounced when constraints are applied to the system in the sense that controlling gates are included in the feedback path. The nature and definition of memory and perception in such nets, and the response of the net to sequences of inputs is also presented and discussed. In conclusion, a simple probabilistic analysis is developed so as to provide a basis for a general understanding of dynamic networks of this kind.

Item Type: Thesis (Doctor of Philosophy (PhD))
Thesis advisor: Aleksander, I.
DOI/Identification number: 10.22024/UniKent/01.02.94337
Additional information: This thesis has been digitised by EThOS, the British Library digitisation service, for purposes of preservation and dissemination. It was uploaded to KAR on 25 April 2022 in order to hold its content and record within University of Kent systems. It is available Open Access using a Creative Commons Attribution, Non-commercial, No Derivatives ( licence so that the thesis and its author, can benefit from opportunities for increased readership and citation. This was done in line with University of Kent policies ( If you feel that your rights are compromised by open access to this thesis, or if you would like more information about its availability, please contact us at and we will seriously consider your claim under the terms of our Take-Down Policy (
Uncontrolled keywords: feedback networks, adaptive logic circuits
Subjects: T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
SWORD Depositor: SWORD Copy
Depositing User: SWORD Copy
Date Deposited: 23 May 2023 11:31 UTC
Last Modified: 23 May 2023 11:31 UTC
Resource URI: (The current URI for this page, for reference purposes)

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