Ontogenic Neural Networks for Avionics Applications

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$50,000.00
Award Year:
1993
Program:
SBIR
Phase:
Phase I
Contract:
n/a
Agency Tracking Number:
20127
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
Accurate Automation Corp
7001 Shallowford Road, Chattanooga, TN, 37421
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Kevin Priddy, Ph.d.
(615) 894-4646
Business Contact:
() -
Research Institution:
n/a
Abstract
The study of neural networks which possess the capability to learn and grow with little or no supervision will be explored during this research effort. These networks exhibit ontogenic behavior and are termed ontogenic neural networks. This reasearch effort explores the use of hybrid neural network structures which are capable of self-organization, feature discovery and self generation in a composite architecture which is capable of solving pattern recognition tasks. These networks will be examined for suitability in automatic target recognition, threat assessment, route planning or another problem selected by the Air Force and Accurate Automation. The ontogenic neural network developed in this effort will be thoroughly examined for learning rate, generalization capability, classification accuracy, representation of higher order relationships, self-organization ability and hardware implementation.

* information listed above is at the time of submission.

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