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Infinitely large, randomly wired sensors cannot predict their input unless they are close to deterministic.

Sarah Marzen1

  • 1Department of Physics, Physics of Living Systems Group, Massachusetts Institute of Technology, Cambridge, MA, United States of America.

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|August 30, 2018
PubMed
Summary

Larger randomly wired sensors are not inherently predictive. Only nearly deterministic random sensors can capture significant input information, suggesting structure is key for predictive sensing.

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Area of Science:

  • Complex systems
  • Information theory
  • Sensor technology

Background:

  • Predictive sensors are crucial for scientific advancement.
  • The relationship between sensor size, wiring randomness, and predictive capability is not well understood.

Purpose of the Study:

  • To investigate if increasing the size of randomly wired sensors improves their predictive ability.
  • To determine the conditions under which random sensor networks can predict their input.

Main Methods:

  • Theoretical analysis of infinitely large, randomly wired sensor networks.
  • Information-theoretic measures to quantify predictive information.

Main Results:

  • Infinitely large, random sensors are generally nonspecific and nonpredictive.
  • Predictivity emerges only when random sensors approach deterministic behavior.
  • Nearly deterministic random sensors can capture approximately 10% of input information in typical environments.

Conclusions:

  • Sensor size alone does not guarantee predictive power in random networks.
  • A high degree of determinism is necessary for randomly wired sensors to be predictive.
  • The findings have implications for designing effective predictive sensing systems.