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    A Novel Pattern Classification Scheme using the Baker's Map


    Rogers, Alan, Keating, John and Shorten, Robert N. (2002) A Novel Pattern Classification Scheme using the Baker's Map. Neurocomputing, 55 (3). pp. 779-786.

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    Abstract

    We demonstrate a novel application of nonlinear systems in the design of pattern classification systems. We show that pattern classification systems can be designed based upon training algorithms designed to control the qualitative behaviour of a nonlinear system. Our paradigm is illustrated by means of a simple chaotic system-the Baker's map. Algorithms for training the system are presented and examples are given to illustrate the operation and learning of the system for pattern classification tasks.
    Item Type: Article
    Keywords: Chaos, Pattern Recognition, Pattern Classification
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Item ID: 39
    Depositing User: Dr Tomas Ward
    Date Deposited: 25 Jul 2002
    Journal or Publication Title: Neurocomputing
    Publisher: Elsevier
    Refereed: Yes
    URI: https://mu.eprints-hosting.org/id/eprint/39
    Use Licence: This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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