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:10.1117/12.343067

22 March 1999 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 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks; (1999) https://doi.org/10.1117/12.343067
Event: Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks: Neural Networks Fuzzy Systems, Evolutionary Systems and Virtual Re, 1998, Stockholm, Sweden

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 considerably 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.

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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 3728, Ninth Workshop on Virtual Intelligence/Dynamic Neural Networks, (22 March 1999); https://doi.org/10.1117/12.343067

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