An Alternative Computation of the Entropy of 1D Signals Based on Geometric Properties

  • Cristian Bonini Center of Research, Development and Innovation in Electric Energy, Universidad Tecnológica Nacional Facultad Regional General Pacheco, Argentina
  • Andrea Rey Center of Signal and Image Processing, Universidad Tecnológica Nacional Facultad Regional Buenos Aires, Buenos Aires, Argentina http://orcid.org/0000-0002-9185-1382
  • Dino Otero Center of Vehicle Research, Development and Innovation, Universidad Tecnológica Nacional Facultad Regional General Pacheco, Argentina http://orcid.org/0000-0003-1950-3823
  • Ariel Amadio Center of Vehicle Research, Development and Innovation, Universidad Tecnológica Nacional Facultad Regional General Pacheco, Argentina
  • Manuel García Blesa Center of Signal and Image Processing, Universidad Tecnológica Nacional Facultad Regional Buenos Aires, Argentina
  • Walter Legnani Center of Signal and Image Processing, Universidad Tecnológica Nacional Facultad Regional Buenos Aires, Argentina http://orcid.org/0000-0002-6949-0728
Keywords: Order Pattern Distribution, Permutation Entropy, Symbolic Dynamics, Signal Entropy, Data Points Geometry

Abstract

The objective of this work is to present a novel methodology based on the computation of a couple of geometric characteristics of the position of the data points in 1D signal to propose an alternative estimation of signal entropy. The conditions to be fulfilled by the signal are minimal; only those necessary to meet the sampling theorem requirement are enough. This work shows some examples in which the proposed methodology can distinguish among signals that cannot be differentiated by other in-use alternatives. Additionally an original example where the usual ordinal pattern algorithm to compute entropy is not applicable, is presented and analyzed. The proposal developed through this work carries some advantages over other alternatives and constitutes a true advancement in the pathway to compute the distribution function of the sequential points of 1D signals later used to compute the entropy of the signal.

References

Saddon T Ahmad, M Kotb, Idris H Salih, and Hewa Y Abdullah. Backbending phenomena in even–even 162-172 Hf isotopes. Physics of Atomic Nuclei, 84(1):18–28, 2021.

TV Alenicheva, P Kabina, IA Mitropolsky, and TM Tyukavina. Iaea nuclear data section. Wagramer strasse5, A-1400 Viena, INDC (CCP), page 439, 2004.

Christoph Bandt and Bernd Pompe. Permutation entropy: a natural complexity measure for time series. Physical Review Letters, 88(17):174102, 2002.

George Bergman. A number system with an irrational base. Mathematics Magazine, 31(2):98–110, 1957.

R Budaca and AA Raduta. Semi-microscopic description of the double backbending in some deformed even–even rare earth nuclei. Journal of Physics G: Nuclear and Particle Physics, 40(2):025109, 2013.

Zhe Chen, Yaan Li, Hongtao Liang, and Jing Yu. Improved permutation entropy for measuring complexity of time series under noisy condition. Complexity, 2019, 2019.

Leon O. Chua. A glimpse of nonlinear phenomena from Chua’s oscillator. Philosophical Transactions of the Royal Society of London. Series A: Physical and Engineering Sciences, 353(1701):3–12, 1995.

David Cuesta-Frau. Using the information provided by forbidden ordinal patterns in permutation entropy to reinforce time series discrimination capabilities. Entropy, 22(5):494, 2020.

R Mà Diamond, FS Stephens, and WJ Swiatecki. Centrifugal stretching of nuclei. Physics Letters, 2(4), 1964.

Hans Frauenfelder and Ernest M. Henley. Subatomic physics. Prentice-Hall, Inc., Englewood Cliffs, NJ, 1974.

Mo Ao J Mariscotti, Gertrude Scharff-Goldhaber, and Brian Buck. Phenomenological analysis of ground-state bands in even-even nuclei. Physical Review, 178(4):1864, 1969.

Lederer C. Michael, Virginia S. Shirley, et al. Table of Isotopes. John Wiley & Sons, 1978.

Otto E. Rossler. The chaotic hierarchy. Zeitschrift f¨ur Naturforschung A, 38(7):788–801, 1983.

Osvaldo A. Rosso and Cristina Masoller. Detecting and quantifying temporal correlations in stochastic resonance via information theory measures. The European Physical Journal B, 69(1):37–43, 2009.

Osvaldo A. Rosso, Felipe Olivares, Luciano Zunino, Luciana De Micco, Andr´e L. Aquino, Angelo Plastino, and Hilda A. Larrondo. Characterization of chaotic maps using the permutation Bandt-Pompe probability distribution. The European Physical Journal B, 86(4):1–13, 2013.

Alexey Stakhov. The importance of the golden number for mathematics and computer science: Exploration of the Bergman’s system and the Stakhov’s ternary mirror-symmetrical system (numeral systems with irrational bases). Journal of Advances in Mathematics and Computer Science, 18(3):1–34, 2016.

Francisco Traversaro, Francisco O. Redelico, Marcelo R. Risk, Alejandro C. Frery, and Osvaldo A. Rosso. Bandt-Pompe symbolization dynamics for time series with tied values: A data-driven approach. Chaos: An Interdisciplinary Journal of Nonlinear Science, 28(7):075502–1–14, 2018.

Valentina A. Unakafova and Karsten Keller. Efficiently measuring complexity on the basis of real-world data. Entropy, 15(10):4392–4415, 2013.

Massimiliano Zanin, Luciano Zunino, Osvaldo A. Rosso, and David Papo. Permutation entropy and its main biomedical and econophysics applications: a review. Entropy, 14(8):1553–1577, 2012.

Hristo Zhivomirov. A method for colored noise generation. Romanian Journal of Acoustics and Vibration, 15(1):14–19, 2018.

Published
2022-06-19
How to Cite
Bonini, C., Rey, A., Otero, D., Amadio, A., García Blesa, M., & Legnani, W. (2022). An Alternative Computation of the Entropy of 1D Signals Based on Geometric Properties. Statistics, Optimization & Information Computing, 10(4), 998-1020. https://doi.org/10.19139/soic-2310-5070-1523
Section
Research Articles