Accession Number : ADA265105


Title :   Representation and Processing of Acoustic Information in a Biomimetic Neural Network


Corporate Author : NAVAL COMMAND CONTROL AND OCEAN SURVEILLANCE CENTER RDT AND E DIV SAN DIEGO CA


Personal Author(s) : Roitblat, H L ; Moore, P W ; Helwig, D A ; Nachtigall, P E


Full Text : https://apps.dtic.mil/dtic/tr/fulltext/u2/a265105.pdf


Report Date : Jan 1992


Pagination or Media Count : 13


Abstract : The effectiveness of artificial neural network models depends strongly on the way in which the information to be learned is presented to the network. Use of biologically relevant mechanisms is likely to yield effective syntactic systems as well as understanding the performance of biological systems. We developed a model of the dolphin cochlea and used this model to produce the representations used by a neural network to model the delayed matching-to-sample performance of a bottlenosed dolphin. The model yielded psychophysical functions and matching choice accuracy similar to those obtained from the dolphin.... Artificial neural networks (AN-N), Echolocation Gateway- integrator neural network (GIN)


Descriptors :   *SOUND TRANSMISSION , *ARTIFICIAL INTELLIGENCE , *ANATOMICAL MODELS , *COCHLEA , FUNCTIONS , REPRINTS , HIGH FREQUENCY , NEURAL NETS , YIELD , SYSTEMS APPROACH , NOISE , DOLPHINS(MAMMALS) , PSYCHOPHYSICS , SELECTION , SONAR ECHOES , MATCHING , INTEGRATORS , ACOUSTICS , ACOUSTIC SIGNALS , MODELS , NETWORKS , SIGNAL TO NOISE RATIO , ACCURACY


Subject Categories : Biological Oceanography
      Cybernetics
      Acoustics


Distribution Statement : APPROVED FOR PUBLIC RELEASE