Title :
The Lockheed probabilistic neural network processor
Author :
Washburne, T.P. ; Okamura, M.M. ; Specht, D.F. ; Fisher, W.A.
Author_Institution :
Lockheed Missiles & Space Co., Huntsville, AL, USA
Abstract :
The probabilistic neural network processor (PNNP) is a custom neural network parallel processor optimized for the high-speed execution (three billion connections per second) of the probabilistic neural network (PNN) paradigm. The PNNP´s massively parallel circuitry can solve pattern recognition and classification problems many orders of magnitude faster than a software simulation of the PNN paradigm. When combined with the instant learning capability of the PNN paradigm, full investigations of large database problems can be done in a very short time. Real-time devices may be attached to the PNNP to show adaptability of the classifier in a dynamic environment
Keywords :
neural nets; parallel architectures; parallel machines; pattern recognition; adaptability; classification; classifier; dynamic environment; instant learning; neural network parallel processor; pattern recognition; probabilistic neural network processor; software simulation; three billion connections per second; Algorithm design and analysis; Backplanes; Backpropagation algorithms; Circuit simulation; Neural network hardware; Neural networks; Neurofeedback; Pattern recognition; Read-write memory; Runtime environment;
Conference_Titel :
Neural Networks, 1991., IJCNN-91-Seattle International Joint Conference on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-0164-1
DOI :
10.1109/IJCNN.1991.155232