Application of graph theory for identifying connectivity patterns in human brain networks: a systematic review
Background: Analysis of the human connectome using functional magnetic resonance
imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to …
imaging (fMRI) started in the mid-1990s and attracted increasing attention in attempts to …
[HTML][HTML] The dynamic functional connectome: State-of-the-art and perspectives
Resting-state functional magnetic resonance imaging (fMRI) has highlighted the rich
structure of brain activity in absence of a task or stimulus. A great effort has been dedicated …
structure of brain activity in absence of a task or stimulus. A great effort has been dedicated …
Time-series clustering–a decade review
Clustering is a solution for classifying enormous data when there is not any early knowledge
about classes. With emerging new concepts like cloud computing and big data and their vast …
about classes. With emerging new concepts like cloud computing and big data and their vast …
The trilemma among CO2 emissions, energy use, and economic growth in Russia
This paper examines the relationship among CO2 emissions, energy use, and GDP in
Russia using annual data ranging from 1990 to 2020. We first conduct time-series analyses …
Russia using annual data ranging from 1990 to 2020. We first conduct time-series analyses …
k-shape: Efficient and accurate clustering of time series
The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …
substantial interest in the analysis and mining of time series. Clustering is one of the most …
TSclust: An R package for time series clustering
P Montero, JA Vilar - Journal of Statistical Software, 2015 - jstatsoft.org
Time series clustering is an active research area with applications in a wide range of fields.
One key component in cluster analysis is determining a proper dissimilarity measure …
One key component in cluster analysis is determining a proper dissimilarity measure …
Deep time-series clustering: A review
We present a comprehensive, detailed review of time-series data analysis, with emphasis on
deep time-series clustering (DTSC), and a case study in the context of movement behavior …
deep time-series clustering (DTSC), and a case study in the context of movement behavior …
[BOK][B] Modern algorithms of cluster analysis
ST Wierzchoń, MA Kłopotek - 2018 - Springer
This chapter characterises the scope of this book. It explains the reasons why one should be
interested in cluster analysis, lists major application areas, basic theoretical and practical …
interested in cluster analysis, lists major application areas, basic theoretical and practical …
Fast and accurate time-series clustering
The proliferation and ubiquity of temporal data across many disciplines has generated
substantial interest in the analysis and mining of time series. Clustering is one of the most …
substantial interest in the analysis and mining of time series. Clustering is one of the most …
Clustering of time series data—a survey
TW Liao - Pattern recognition, 2005 - Elsevier
Time series clustering has been shown effective in providing useful information in various
domains. There seems to be an increased interest in time series clustering as part of the …
domains. There seems to be an increased interest in time series clustering as part of the …