Accession Number:

ADA179285

Title:

Optical Relational-Graph Rule-Based Processor for Structural-Attribute Knowledge Bases,

Descriptive Note:

Corporate Author:

CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF ELECTRICAL AND COMPUTER ENGINEERING

Personal Author(s):

Report Date:

1986-09-15

Pagination or Media Count:

7.0

Abstract:

An optical relational-graph or decision-net processor is advanced, and one optical system design for such a processor is provided. The general description of this processor is provided as well as two designs for a specific case study. A rule-based design of a knowledge base of facts using structural rather than functional attributes of the object is detailed. A general technique is advanced to organize a fact-based knowledge base into a rule-based knowledge base using structural rather than functional attributes. A multiclass 3-D distorted object identification and classification problem is considered as our case study. A general relational-graph design methodology is advanced, and specific designs for our case study are then presented. Multidecision and binary relational-graph designs are advanced, and impressive initial simulation results with each are noted. Reprint.

Subject Categories:

  • Optics

Distribution Statement:

APPROVED FOR PUBLIC RELEASE