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» Modeling synchronized time series
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TNN
2010
174views Management» more  TNN 2010»
13 years 4 months ago
Equivalences between neural-autoregressive time series models and fuzzy systems
Soft computing (SC) emerged as an integrating framework for a number of techniques that could complement one another quite well (artificial neural networks, fuzzy systems, evolutio...
José Luis Aznarte, José Manuel Ben&i...
IDEAL
2004
Springer
14 years 3 months ago
Combining Local and Global Models to Capture Fast and Slow Dynamics in Time Series Data
Many time series exhibit dynamics over vastly different time scales. The standard way to capture this behavior is to assume that the slow dynamics are a “trend”, to de-trend t...
Michael Small
KDD
2004
ACM
147views Data Mining» more  KDD 2004»
14 years 3 months ago
Clustering time series from ARMA models with clipped data
Clustering time series is a problem that has applications in a wide variety of fields, and has recently attracted a large amount of research. In this paper we focus on clustering...
Anthony J. Bagnall, Gareth J. Janacek
AINA
2008
IEEE
14 years 4 months ago
Missing Value Estimation for Time Series Microarray Data Using Linear Dynamical Systems Modeling
The analysis of gene expression time series obtained from microarray experiments can be effectively exploited to understand a wide range of biological phenomena from the homeostat...
Connie Phong, Raul Singh
CSDA
2006
117views more  CSDA 2006»
13 years 9 months ago
Exact maximum likelihood estimation of structured or unit root multivariate time series models
TheexactlikelihoodfunctionofaGaussianvectorautoregressive-movingaverage(VARMA)model is evaluated in two nonstandard cases: (a) a parsimonious structured form, such as obtained in ...
Guy Mélard, Roch Roy, Abdessamad Saidi