RAM-based neural networks for data mining applications

Kenneth I. Agehed; Age J. Eide; Thomas Lindblad; Clark S. Lindsey; Geza Szekely; Joakim T. A. Waldemark; Karina E. Waldemark

doi:10.1117/12.304833

25 March 1998 RAM-based neural networks for data mining applications

Kenneth I. Agehed, Age J. Eide, Thomas Lindblad, Clark S. Lindsey, Geza Szekely, Joakim T. A. Waldemark, Karina E. Waldemark

Author Affiliations +

Proceedings Volume 3390, Applications and Science of Computational Intelligence; (1998) https://doi.org/10.1117/12.304833
Event: Aerospace/Defense Sensing and Controls, 1998, Orlando, FL, United States

Abstract

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.

Citation Download Citation

Kenneth I. Agehed, Age J. Eide, Thomas Lindblad, Clark S. Lindsey, Geza Szekely, Joakim T. A. Waldemark, and Karina E. Waldemark "RAM-based neural networks for data mining applications", Proc. SPIE 3390, Applications and Science of Computational Intelligence, (25 March 1998); https://doi.org/10.1117/12.304833

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