ON DYNAMIC SWITCHING IN ONE-DIMENSIONAL ITERATIVE LOGIC NETWORKS

Abstract

A SITN is a cascade of identical finite automata such that the i(th) power automation receives an x sub i input from the outside world and a y sub i input from its left neighbor, and produces a z sub i output to the outside world and a y sub il output to its right neighbor. We prove three main theorems: (1) For every integer k there is a cell definition such that a corresponding SITN either can or cannot switch from equilibrium to a cycling condition following a single x sub i change according as n equal to or less than k or n > k, respectively; (2) there do not exist algorithms to tell whether or not a given cell definition admits of a SITN that can start from equilibrium and following a single x sub i change either (a) switch into a cycling con dition, or (b) put out a z sub i 1 during a switching transient; and (3) there do not exist algorithms to tell whether or not a given SITN cell definition must have every switching transient following a single x sub i change from equilibrium either (a) die out a bounded number of cells to the right of the change, or (b) extend all the way to the SITN boundary. All theorems are proved constructively on finite-state diagrams, and (2) and (3) hinge on an embedding of Minsky's Post Tag system results into such diagrams. We conclude with several iterative network equivalence demonstrations.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1963
Accession Number
AD0408414

Entities

People

  • W. L. Kilmer

Tags

Communities of Interest

  • Advanced Electronics
  • Energy and Power Technologies
  • Materials and Manufacturing Processes
  • Space

DTIC Thesaurus Topics

  • Air Force
  • Automata
  • Boundaries
  • Brain
  • Command And Control
  • Contracts
  • Crystal Structure
  • Electronics
  • Government Procurement
  • Governments
  • Logic Gates
  • Machines
  • Nervous System
  • New York
  • Sequences
  • Switching
  • United States

Readers

  • Electrical Engineering
  • Mathematical Modeling and Probability Theory.