High Speed Optical Higher Order Neural Networks for Discovering Data Trends and Patterns in Very Large Databases

High Speed Optical Higher Order Neural Networks for Discovering Data Trends and Patterns in Very Large Databases

David R. Selviah (University College London, UK)
DOI: 10.4018/978-1-60566-058-5.ch063
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Abstract

This chapter describes the progress in using optical technology to construct high-speed artificial higher order neural network systems. The chapter reviews how optical technology can speed up searches within large databases in order to identify relationships and dependencies between individual data records, such as financial or business time-series, as well as trends and relationships within them. Two distinct approaches in which optics may be used are reviewed. In the first approach, the chapter reviews current research replacing copper connections in a conventional data storage system, such as a several terabyte RAID array of magnetic hard discs, by optical waveguides to achieve very high data rates with low crosstalk interference. In the second approach, the chapter reviews how high speed optical correlators with feedback can be used to realize artificial higher order neural networks using Fourier Transform free space optics and holographic database storage.

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