Complexity and entropy representation for machine component diagnostics.
The Complexity-entropy causality plane (CECP) is a parsimonious representation space for time series. It has only two dimensions: normalized permutation entropy ([Formula: see text]) and Jensen-Shannon complexity ([Formula: see text]) of a time series. This two-dimensional representation allows for...
Main Authors: | Srinivasan Radhakrishnan, Yung-Tsun Tina Lee, Sudarsan Rachuri, Sagar Kamarthi |
---|---|
Format: | Article |
Language: | English |
Published: |
Public Library of Science (PLoS)
2019-01-01
|
Series: | PLoS ONE |
Online Access: | https://doi.org/10.1371/journal.pone.0217919 |
Similar Items
-
Exploration of physiological sensors, features, and machine learning models for pain intensity estimation.
by: Fatemeh Pouromran, et al.
Published: (2021-01-01) -
Health Care in US: A Combined Simulation Methodology to Assess the Effectiveness of Home-Monitoring Programmes
by: Srinivasan Radhakrishnan, et al.
Published: (2015-09-01) -
Standard Data-Based Predictive Modeling for Power Consumption in Turning Machining
by: Seung-Jun Shin, et al.
Published: (2018-02-01) -
Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.
by: Srinivasan Radhakrishnan, et al.
Published: (2017-01-01) -
Correction: Novel keyword co-occurrence network-based methods to foster systematic reviews of scientific literature.
by: Srinivasan Radhakrishnan, et al.
Published: (2017-01-01)