Paper
4 April 1997 Application of highly parallel computing hardware to pattern recognition problems
Kevin L. Priddy, Karl Mathia, Timothy Robinson, Robert M. Pap
Author Affiliations +
Abstract
Neural networks are well known for their ability to perform pattern recognition tasks. This paper discusses the use of parallel neural network hardware for performing pattern recognition tasks. We address the need for neural network hardware and how it can dramatically improve system performance both in training and in actual applications. The use of specialized parallel processing hardware is discussed as well as alternative hardware and software approaches. Finally we give some comparisons between multi-processor computer architecture, Pentium class microcomputers and custom hardware.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kevin L. Priddy, Karl Mathia, Timothy Robinson, and Robert M. Pap "Application of highly parallel computing hardware to pattern recognition problems", Proc. SPIE 3077, Applications and Science of Artificial Neural Networks III, (4 April 1997); https://doi.org/10.1117/12.271485
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KEYWORDS
Pattern recognition

Neural networks

Parallel computing

Computer architecture

Parallel processing

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