Fuzzy representational structures for trend based analysis of time series clustering and classification

2021 ◽  
pp. 106991
Author(s):  
Johnpaul C.I. ◽  
Munaga V.N.K. Prasad ◽  
S. Nickolas ◽  
G.R. Gangadharan
Keyword(s):  
Time Series ◽  
Time Series Clustering ◽  
Clustering And Classification ◽  
Analysis Of Time Series

scholarly journals Time Series Clustering and Classification

Technometrics ◽  
2021 ◽  
Vol 63 (3) ◽  
pp. 441-441
Author(s):  
Srishti Vishwakarma ◽  
Vyacheslav Lyubchich
Keyword(s):  
Time Series ◽  
Time Series Clustering ◽  
Clustering And Classification

scholarly journals Time Series Clustering and Classification

2019 ◽  
Author(s):  
Elizabeth Ann Maharaj ◽  
Pierpaolo D'Urso ◽  
Jorge Caiado
Keyword(s):  
Time Series ◽  
Time Series Clustering ◽  
Clustering And Classification

Correlation in the heart rate data

1998 ◽  
Vol 2 ◽  
pp. 141-148
Author(s):  
J. Ulbikas ◽  
A. Čenys ◽  
D. Žemaitytė ◽  
G. Varoneckas
Keyword(s):  
Nonlinear Dynamics ◽  
Experimental Data ◽  
Heart Rate ◽  
Time Series ◽  
Cardiovascular Function ◽  
Statistical Properties ◽  
Rate Data ◽  
Heart Rate Data ◽  
Dynamical Nature ◽  
Analysis Of Time Series

Variety of methods of nonlinear dynamics have been used for possibility of an analysis of time series in experimental physiology. Dynamical nature of experimental data was checked using specific methods. Statistical properties of the heart rate have been investigated. Correlation between of cardiovascular function and statistical properties of both, heart rate and stroke volume, have been analyzed. Possibility to use a data from correlations in heart rate for monitoring of cardiovascular function was discussed.

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