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Proceedings Paper

Neural networks for matched filter selection and synthesis
Author(s): Peter T. Kazlas; Peter T. Monsen
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Paper Abstract

Neural networks are investigated for real-time matched filter selection in an optical correlator system. The input to the neural network is a sample space of the optical Fourier transform and the output is a pointer to the correct matched filter. Smaller feedforward network models were ported to analog neural hardware. Simulation and hardware results are discussed. Some architecture recommendations are suggested, specifically an associative memory for filter synthesis.

Paper Details

Date Published: 16 September 1992
PDF: 6 pages
Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); doi: 10.1117/12.140049
Show Author Affiliations
Peter T. Kazlas, Charles Stark Draper Lab., Inc. (United States)
Peter T. Monsen, Charles Stark Draper Lab., Inc. (United States)


Published in SPIE Proceedings Vol. 1709:
Applications of Artificial Neural Networks III
Steven K. Rogers, Editor(s)

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