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  • Cognitive Memory Network

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    63211_1.pdf (302.2Kb)
    Author(s)
    James, AP
    Dimitrijev, S
    Griffith University Author(s)
    Dimitrijev, Sima
    James, Alex P.
    Year published
    2010
    Metadata
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    Abstract
    A resistive memory network that has no crossover wiring is proposed to overcome the hardware limitations to size and functional complexity that is associated with conventional analogue neural networks. The proposed memory network is based on simple network cells that are arranged in a hierarchical modular architecture. Cognitive functionality of this network is demonstrated by an example of character recognition. The network is trained by an evolutionary process to completely recognise characters deformed by random noise, rotation, scaling and shifting.A resistive memory network that has no crossover wiring is proposed to overcome the hardware limitations to size and functional complexity that is associated with conventional analogue neural networks. The proposed memory network is based on simple network cells that are arranged in a hierarchical modular architecture. Cognitive functionality of this network is demonstrated by an example of character recognition. The network is trained by an evolutionary process to completely recognise characters deformed by random noise, rotation, scaling and shifting.
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    Journal Title
    Electronics Letters
    Volume
    46
    Issue
    10
    DOI
    https://doi.org/10.1049/el.2010.0279
    Copyright Statement
    © 2010 IET. This paper is a postprint of a paper submitted to and accepted for publication in Electronics Letters and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at IET Digital Library
    Subject
    Circuits and Systems
    Artificial Intelligence and Image Processing
    Electrical and Electronic Engineering
    Communications Technologies
    Publication URI
    http://hdl.handle.net/10072/32185
    Collection
    • Journal articles

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