This work put forward a distance measure based on cepstral coefficients for time series data clustering. The main instrument for carrying out this task is model ...
Jul 15, 2024 · After estimation, the estimated cepstral distance measure is given as an input to a clustering method to produce the disjoint groups of data.
Time series clustering methods are based on the calculation of suitable similarity measures which identify the distance between two or more time series. These ...
Oct 22, 2024 · After estimation, the estimated cepstral distance measure is given as an input to a clustering method to produce the disjoint groups of data.
Multivariate time series (MTS) data are ubiquitous in science and daily life, and how to measure their similarity is a core part of MTS analyzing process. Many ...
Clustering of biological time series by cepstral coefficients based distances. A. Savvides, V. Promponas, and K. Fokianos. Pattern Recognition, 41 (7): 2398 ...
In this paper a methodology to cluster time series based on measurement data is described. In particular, we propose a distance for stochastic models based ...
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Time series clustering consists of using an appropriate similarity measure (distance metric) for unsupervised grouping of data that are observed over time.
A novel methodology is proposed for clustering multivariate time series data using energy distance defined in Székely and Rizzo (2013).
[PDF] The relationship between clustering and forecast reconciliation
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Clustering of biological time series by cepstral coefficients based distances. Pattern Recognition,. 41(7):2398–2412, 2008. J. A. Vilar and S. Pértega ...