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Rapp PE, Cellucci CJ, Korslund KE, et al. Effective normalization of complexity measurements for epoch length and sampling frequency. Phys Rev E Stat Nonlin Soft Matter Phys. 2001;64(1):016209doi: 10.1103/PhysRevE.64.016209.
Rapp, P. E., Cellucci, C. J., Korslund, K. E., Watanabe, T. A., & Jiménez-Montaño, M. A. (2001). Effective normalization of complexity measurements for epoch length and sampling frequency. Physical review. E, Statistical, nonlinear, and soft matter physics, 64(1), 016209. https://doi.org/10.1103/PhysRevE.64.016209
Rapp, P E, et al. "Effective normalization of complexity measurements for epoch length and sampling frequency." Physical review. E, Statistical, nonlinear, and soft matter physics vol. 64,1 (2001): 016209. doi: https://doi.org/10.1103/PhysRevE.64.016209
Rapp PE, Cellucci CJ, Korslund KE, Watanabe TA, Jiménez-Montaño MA. Effective normalization of complexity measurements for epoch length and sampling frequency. Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Jul;64(1):016209. doi: 10.1103/PhysRevE.64.016209. Epub 2001 Jun 14. PMID: 11461369.
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Phys Rev E Stat Nonlin Soft Matter Phys. 2001 Jul;64(1):016209. doi: 10.1103/PhysRevE.64.016209. Epub 2001 Jun 14.

Effective normalization of complexity measurements for epoch length and sampling frequency.

Physical review. E, Statistical, nonlinear, and soft matter physics

P E Rapp, C J Cellucci, K E Korslund, T A Watanabe, M A Jiménez-Montaño

Affiliations

  1. Department of Pharmacology and Physiology, Medical College of Pennsylvania Hahnemann University, Philadelphia, Pennsylvania 19129, USA. [email protected]

PMID: 11461369 DOI: 10.1103/PhysRevE.64.016209

Abstract

The algorithmic complexity of a symbol sequence is sensitive to the length of the message. Additionally, in those cases where the sequence is constructed by the symbolic reduction of an experimentally observed wave form, the corresponding value of algorithmic complexity is also sensitive to the sampling frequency. In this contribution, we present definitions of algorithmic redundancy that are sequence-sensitive generalizations of Shannon's original definition of information redundancy. In contrast with algorithmic complexity, we demonstrate that algorithmic redundancy is not sensitive to message length or to observation scale (sampling frequency) when stationary systems are examined.

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