MACHINE LEARNING USING AN ADAPTIVE-NETWORK FOR PATTERN RECOGNITION

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$532,661.00
Award Year:
1989
Program:
SBIR
Phase:
Phase II
Contract:
n/a
Award Id:
4465
Agency Tracking Number:
4465
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
4126 Linden Ave, Dayton, OH, 45432
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
n/a
Principal Investigator:
Dr Barry Deer
(513) 252-5601
Business Contact:
() -
Research Institute:
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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