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Alternative neural network training methods [active sonar processing]

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2 Author(s)
Porto, V.W. ; Orincon Corp., San Diego, CA, USA ; Fogel, D.B.

Investigates three potential neural network training algorithms in processing active sonar returns. Although all three methods generate reasonable probabilities of detection and false alarm in discriminating between man-made objects and background events, the stochastic training methods of simulated annealing and evolutionary programming outperform backpropagation

Published in:

IEEE Expert  (Volume:10 ,  Issue: 3 )

Date of Publication:

Jun 1995

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