Inferring Statistical Complexity

James P. Crutchfield and Karl Young
Physics Department
University of California
Berkeley, California 94720, USA

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 super-universality that refers only to the entropy and complexity of a data stream.

Citation

J. P. Crutchfield and K. Young, Inferring Statistical Complexity, Physical Review Letters 63 (1989) 105-108.

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