N. Binenbaum, L. Dias, P. Hsieh, C.H. Ju, S. Markel, J. Pearson, H. Taylor
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Neural networks for signal/image processing using the Princeton Engine multi-processor
The authors describe a modular neural network system for the removal of impulse noise from the composite video signal of television receivers, and the use of the Princeton Engine multi-processor for real-time performance assessment. This system out-performs alternative methods, such as median filters and matched filters. The system uses only eight neurons, and can be economically implemented in VLSI.<>
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