Ontogenic Neural Networks for Avionics Applications

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: N/A
Agency Tracking Number: 20127
Amount: $50,000.00
Phase: Phase I
Program: SBIR
Awards Year: 1993
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
7001 Shallowford Road, Chattanooga, TN, 37421
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Kevin Priddy, Ph.d.
 (615) 894-4646
Business Contact
Phone: () -
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. *

Agency Micro-sites

SBA logo
Department of Agriculture logo
Department of Commerce logo
Department of Defense logo
Department of Education logo
Department of Energy logo
Department of Health and Human Services logo
Department of Homeland Security logo
Department of Transportation logo
Environmental Protection Agency logo
National Aeronautics and Space Administration logo
National Science Foundation logo
US Flag An Official Website of the United States Government