Fundamental Experimental Research on the Dynamics of Physical Networks

Abstract

Objective: We undertook a broad experimental program in fundamental network science. We used a revolutionary experimental approach to observe and analyze the evolution of complex dynamical networks such as pattern formation and control, emergence of complexity, and information processing. Specifically, we studied time delayed Boolean networks implemented experimentally with logic gates on field-programmable gate arrays (FPGAs). We used this experimental platform to create diverse networks of various sizes that display periodic, chaotic, and excitable dynamics and we applied what we learned about these networks to perform information processing and performed more detailed studies of the ultra-long transient behavior of relatively simple networks that have implications for biological networks. In addition, we have explored methods for solving constraint satisfaction problems using autonomous Boolean networks on an FPGA.

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Document Details

Document Type
Technical Report
Publication Date
Jan 20, 2019
Accession Number
AD1070063

Entities

People

  • Daniel J Gauthier

Organizations

  • Duke University

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Artificial Intelligence
  • Artificial Neural Networks
  • Change Detection
  • Communication Systems
  • Complex Systems
  • Computational Science
  • Computers
  • Data Science
  • Differential Equations
  • Digital Data
  • Equations
  • Field Programmable Gate Arrays
  • Information Processing
  • Logic Gates
  • Machine Learning
  • Mathematical Models
  • Military Research
  • Nanosecond Time
  • Network Science
  • Neural Networks
  • Radio Frequency
  • Reservoir Computing
  • Standards

Readers

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  • Parallel and Distributed Computing.
  • Systems Analysis and Design