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» Computing and using residuals in time series models
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AINA
2008
IEEE
13 years 11 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
CVPR
1999
IEEE
14 years 7 months ago
Time-Series Classification Using Mixed-State Dynamic Bayesian Networks
We present a novel mixed-state dynamic Bayesian network (DBN) framework for modeling and classifying timeseries data such as object trajectories. A hidden Markov model (HMM) of di...
Vladimir Pavlovic, Brendan J. Frey, Thomas S. Huan...
BMCBI
2010
118views more  BMCBI 2010»
13 years 5 months ago
Computing H/D-Exchange rates of single residues from data of proteolytic fragments
Background: Protein conformation and protein/protein interaction can be elucidated by solution-phase Hydrogen/ Deuterium exchange (sHDX) coupled to high-resolution mass analysis o...
Ernst Althaus, Stefan Canzar, Carsten Ehrler, Mark...
AUTOMATICA
2006
66views more  AUTOMATICA 2006»
13 years 5 months ago
Robust residual generation for diagnosis including a reference model for residual behavior
: The main goal when synthesizing robust residual generators, for diagnosis and supervision, is to attenuate influence from model uncertainty on the residual while keeping fault de...
Erik Frisk, Lars Nielsen
IWANN
2005
Springer
13 years 10 months ago
Direct and Recursive Prediction of Time Series Using Mutual Information Selection
Abstract. This paper presents a comparison between direct and recursive prediction strategies. In order to perform the input selection, an approach based on mutual information is u...
Yongnan Ji, Jin Hao, Nima Reyhani, Amaury Lendasse