MACHINE LEARNING USING AN ADAPTIVE-NETWORK FOR PATTERN RECOGNITION

Award Information
Agency: Department of Defense
Branch: Air Force
Contract: N/A
Agency Tracking Number: 4465
Amount: $532,661.00
Phase: Phase II
Program: SBIR
Awards Year: 1989
Solicitation Year: N/A
Solicitation Topic Code: N/A
Solicitation Number: N/A
Small Business Information
4126 Linden Ave, Dayton, OH, 45432
DUNS: N/A
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Dr Barry Deer
 (513) 252-5601
Business Contact
Phone: () -
Research Institution
N/A
Abstract
THE EVOLUTION OF HIGH ORDER LANGUAGES FOR ROBOTIC SYSTEMS HAS PROCEEDED TO A POINT WHERE THEIR UTILIZATION IN SOLVING APPLICATIONS PROBLEMS IS TERMED "ARTIFICIAL INTELLIGENCE". HOWEVER A KEY REMAINING TECHNOLOGY PROBLEM FOCUSES ON TECHNIQUES WHICH WILL ALLOW SOFTWARE SYSTEMS TO LEARN AS A FUNCTION OF THEIR UTILIZATION, AND EXPERIENCE. IN THIS SBIR WE PROPOSE RESEARCH TO ENHANCE A PROTOTYPE ADAPTIVE-NETWORK PATTERN RECOGNITION SYSTEM DESIGNED BY SYSTRAN UNDER AN AIR FORCE SUPPORTED RESEARCH PROGRAM. ADAPTIVE NETWORKS ARE AN ALTERNATIVE APPROACH TO AI WHICH MODEL BIOLOGICAL LEARNING SYSTEMS AND HAVE BEEN DEMONSTRATED TO LEARN FROM EXPERIENCE WITHOUT ADDITIONAL PROGRAMMING. THE TASKS SET FORTH IN THE STATEMENT OF WORK WILL ADVANCE A PATTERN RECOGNIZING ADAPTIVE NETWORK FOR FAST REALTIME PROCESSING.

* Information listed above is at the time of submission. *

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