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A digital learning system for tracking pattern features

Reeves, A. P. (1973) A digital learning system for tracking pattern features. Doctor of Philosophy (PhD) thesis, University of Kent. (doi:10.22024/UniKent/01.02.94604) (KAR id:94604)


A novel pattern processing scheme has been investigated which makes use of the motions generated by a window which tracks the lines or contours of a digitised television image of a black/white pattern. The novel features of the proposed scheme are that adaptive learning networks are used for both tracking and classifying. The tracking strategy is learnt from a human teacher.

Here one combines two methods of machine pattern recognition which, in isolation, have a limited performance. These are, 'static learning networks' which have known limitations, and 'programmed tracking systems' in which the pre-programming itself may be limiting. In this combination one avoids some limitations of these systems because pre-programming of strategies is not necessary and feedback exists to make the task of the nets a dynamic one.

The thesis describes a hardware visual input and a special-purpose software system which were developed for this investigation. Also, several new modifications of the SLAM (Stored Logic Adaptive Microcircuit) element are discussed.

Beyond its practical application it is possible to conclude that the system developed here may be useful in the study of hypotheses regarding living animal systems which involve eye movements.

Item Type: Thesis (Doctor of Philosophy (PhD))
DOI/Identification number: 10.22024/UniKent/01.02.94604
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 (
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering > TK7800 Electronics
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: 13 Jul 2023 11:08 UTC
Last Modified: 14 Jul 2023 13:59 UTC
Resource URI: (The current URI for this page, for reference purposes)

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