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16 September 1992 Neural networks for matched filter selection and synthesis
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Peter T. Kazlas and Peter T. Monsen "Neural networks for matched filter selection and synthesis", Proc. SPIE 1709, Applications of Artificial Neural Networks III, (16 September 1992); https://doi.org/10.1117/12.140049
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