3D fractal Hurst exponential estimation for acoustic wave

Julio Cesar Tovar Rodriguez, Ricardo Carreno Aguilera, Miguel Patino Ortiz, Julian Patino Ortiz, Alexander Balankin

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents an estimation for Hurst exponent based on its stochastic and fractal properties. The basic description was considered with respect to fractal description. The estimation technique is a functional, in where the form depends of the whole time series piezoelectric storage. The recursive properties that the Hurst estimation, and the two first probability moments have applicability in systems with memory and time operations restrictions, requiring in each operation to have only one state delayed. Therefore, the data storage has the enough information for the two first moments and the Hurst functional estimation have successfully. The data storage is included in the computational system using Benoit 1.3 software® and conserving the history time sequence, describes the curves that bounded the system, having in natural manner a fractal description without loss its properties.

Original languageEnglish
Title of host publicationICNSC 2016 - 13th IEEE International Conference on Networking, Sensing and Control
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467399753
DOIs
StatePublished - 25 May 2016
Event13th IEEE International Conference on Networking, Sensing and Control, ICNSC 2016 - Mexico City, Mexico
Duration: 28 Apr 201630 Apr 2016

Publication series

NameICNSC 2016 - 13th IEEE International Conference on Networking, Sensing and Control

Conference

Conference13th IEEE International Conference on Networking, Sensing and Control, ICNSC 2016
Country/TerritoryMexico
CityMexico City
Period28/04/1630/04/16

Keywords

  • Hurst coefficient
  • acoustic activity
  • fractals
  • time series

Fingerprint

Dive into the research topics of '3D fractal Hurst exponential estimation for acoustic wave'. Together they form a unique fingerprint.

Cite this