RAM based neural networks for data mining applications

Kenneth Agehed, Åge J. Eide, Thomas Lindblad, Clark S. Lindsey, Géza Székely, Joakim Waldemark, Karina Waldemark

Research output: Contribution to journalConference article


We discuss possible new hardware and software techniques for handling very large databases such as image archives. In particular, we investigate how high capacity solid-state "disks" could be used to speed the database processing by algorithms that require considerable memory space. One such algorithm, for example, called the RAM neural network, or weightless neural network, needs a number of large lookup tables to perform most efficiently. The solid state disks could provide fast storage both for the algorithm and the data. We also briefly discuss development of an algorithm to cluster images of similar objects. This algorithm could also benefit from a large cache of fast memory storage.

Original languageEnglish
Pages (from-to)430-437
Number of pages8
JournalProceedings of SPIE - The International Society for Optical Engineering
Publication statusPublished - Mar 25 1998
EventApplications and Science of Computational Intelligence 1998 - Orlando, United States
Duration: Apr 13 1998Apr 17 1998



  • Database indexing
  • RAM net
  • Solid-state disks
  • Weightless neural networks

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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