Skip to main content
SpringerLink
Log in

Associative Memory Based Image and Object Recognition by Quantum Holography

  • Published:
Open Systems & Information Dynamics

Abstract

A quantum associative memory, much more natural than those of “quantum computers”, is presented. Neural-net-like processing with real-valued variables is transformed into processing with quantum waves. Successful computer simulations of image storage and retrieval are reported. Our Hopfield-like algorithm allows quantum implementation with holographic procedure using present-day quantum-optics techniques. This brings many advantages over classical Hopfield neural nets and quantum computers with logic gates.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

Author information

Authors and Affiliations

  1. Faculty of Engineering and Technology, Multimedia University, MY-75450, Melaka, Malaysia

    Chu Kiong Loo

  2. Institute for Computer Vision & Graphics, Graz University of Technology, Inffeldgasse 16/2, A-8010, Graz, Austria

    Mitja Peruš & Horst Bischof

Authors
  1. Chu Kiong Loo
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Mitja Peruš
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Horst Bischof
    View author publications

    You can also search for this author in PubMed Google Scholar

Rights and permissions

Reprints and permissions

About this article

Cite this article

Loo, C.K., Peruš, M. & Bischof, H. Associative Memory Based Image and Object Recognition by Quantum Holography. Open Systems & Information Dynamics 11, 277–289 (2004). https://doi.org/10.1023/B:OPSY.0000047571.17774.8d

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1023/B:OPSY.0000047571.17774.8d

Keywords

Search

Navigation