Boolean Reasoning and Informed Search in the Minimization of Logic Circuits

Abstract

The minimization of logic circuits has been an important area of research for more than a half century. The approaches taken in this field, however, have for the most part been ad hoc. Boolean techniques have been employed to manipulate formulas, but not to perform symbolic reasoning. Boolean equations are employed principally as icons; they are never solved. The first objective of this dissertation is to apply Boolean reasoning systematically and uniformly to the minimization problem. Boolean reasoning entails the reduction of systems of Boolean equations to a single equation; the single equation is an abstraction, independent of the form of the original equations, upon which a variety of reasoning operations may be performed. The second objective is to apply informed search, which has arisen from research in Artificial Intelligence, to the minimization problem. A circuit specification is reduced to a single equivalent equation called a 1-normal form. It is shown that forming a particular solution for the equation corresponds to deriving a design.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1992
Accession Number
ADA248110

Entities

People

  • James J. Kainec

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Boolean Algebra
  • Circuits
  • Computer Programming
  • Computer Science
  • Computer-Aided Design
  • Computers
  • Heuristic Methods
  • Lisp Programming Language
  • Logic
  • Logic Gates
  • Operating Systems
  • Plastic Explosives
  • Trees (Data Structures)
  • United States Military Academy
  • Very Large Scale Integration

Readers

  • Applied Combinatorial Optimization and Logic Circuit Design.
  • Calculus or Mathematical Analysis
  • Geospatial Intelligence and Artificial Intelligence Analytics

Technology Areas

  • AI & ML
  • AI & ML - Machine Learning Algorithms