Inferring statistical complexity

James P. Crutchfield and Karl Young
Phys. Rev. Lett. 63, 105 – Published 10 July 1989
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Abstract

Statistical mechanics is used to describe the observed information processing complexity of nonlinear dynamical systems. We introduce a measure of complexity distinct from and dual to the information theoretic entropies and dimensions. A technique is presented that directly reconstructs minimal equations of motion from the recursive structure of measurement sequences. Application to the period-doubling cascade demonstrates a form of superuniversality that refers only to the entropy and complexity of a data stream.

  • Received 13 December 1988

DOI:https://doi.org/10.1103/PhysRevLett.63.105

©1989 American Physical Society

Authors & Affiliations

James P. Crutchfield and Karl Young

  • Physics Department, University of California, Berkeley, California 94720

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Issue

Vol. 63, Iss. 2 — 10 July 1989

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