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MACHINE LEARNING USING AN ADAPTIVE-NETWORK FOR PATTERN RECOGNITION

Award Information

Agency:
Department of Defense
Branch:
Air Force
Award ID:
4465
Program Year/Program:
1989 / SBIR
Agency Tracking Number:
4465
Solicitation Year:
N/A
Solicitation Topic Code:
N/A
Solicitation Number:
N/A
Small Business Information
SYSTRAN FEDERAL CORP.
4027 Colonel Glenn Highway Suite 210 Dayton, OH 45431-1672
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Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No
 
Phase 2
Fiscal Year: 1989
Title: MACHINE LEARNING USING AN ADAPTIVE-NETWORK FOR PATTERN RECOGNITION
Agency / Branch: DOD / USAF
Contract: N/A
Award Amount: $532,661.00
 

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.

Principal Investigator:

Dr Barry Deer
5132525601

Business Contact:

Small Business Information at Submission:

Systran Corp.
4126 Linden Ave Dayton, OH 45432

EIN/Tax ID:
DUNS: N/A
Number of Employees:
Woman-Owned: No
Minority-Owned: No
HUBZone-Owned: No