THE STUDY OF MATHEMATICAL MODELS FOR SELF-ORGANIZING SYSTEMS.

Abstract

Emphasis of the work is concentrated on three of the more promising models of self-organizing systems; namely, the cellular model, the linear statistical model and the list structure model. The discussion of the cellular model describes experiments in a two-dimensional rectangular space initially containing binary elements. The experiments gave insight into rules of element behavior that lead to stability and pattern formation. The linear statistical predictor provides a method for determining the structures of time-varying systems within a behavioral class. The list structure model began with an examination of state classes and regular expressions. It became clear early in the study that a primary prerequisite was a language suited to description of such a model capable of being programmed on a computer. It was demonstrated that the second-order predicate logic was a suitable language.

Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1965
Accession Number
AD0610740

Entities

People

  • Aaron Rosenberg
  • Amy L. Eliasoff
  • J. F. White
  • J. Korsh
  • Morris Rubinoff

Organizations

  • University of Pennsylvania

Tags

DTIC Thesaurus Topics

  • Computers
  • Identification
  • Language
  • Linear Systems
  • Mathematical Models
  • Models
  • Self Organizing Systems
  • Two Dimensional

Readers

  • Computational Fluid Dynamics (CFD)
  • Neural Network Machine Learning.
  • Systems Analysis and Design

Technology Areas

  • Space