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TMI
2008
138views more  TMI 2008»
15 years 3 months ago
Dynamic Positron Emission Tomography Data-Driven Analysis Using Sparse Bayesian Learning
A method is presented for the analysis of dynamic positron emission tomography (PET) data using sparse Bayesian learning. Parameters are estimated in a compartmental framework usin...
Jyh-Ying Peng, John A. D. Aston, R. N. Gunn, Cheng...
JAIR
2010
108views more  JAIR 2010»
15 years 2 months ago
Kalman Temporal Differences
This paper deals with value (and Q-) function approximation in deterministic Markovian decision processes (MDPs). A general statistical framework based on the Kalman filtering pa...
Matthieu Geist, Olivier Pietquin
INTERSPEECH
2010
14 years 11 months ago
Efficient HMM-based estimation of missing features, with applications to packet loss concealment
In this paper, we present efficient HMM-based techniques for estimating missing features. By assuming speech features to be observations of hidden Markov processes, we derive a mi...
Bengt J. Borgström, Per Henrik Borgström...
CVRMED
1997
Springer
15 years 8 months ago
Medical image segmentation using topologically adaptable surfaces
E cient and powerful topologically adaptable deformable surfaces can be created by embedding and de ning discrete deformable surface models in terms of an A ne Cell Decomposition (...
Tim McInerney, Demetri Terzopoulos
AUTOMATICA
2008
123views more  AUTOMATICA 2008»
15 years 4 months ago
Identification with stochastic sampling time jitter
This work investigates how stochastic sampling jitter noise affects the result of system identification, and proposes a modification of known approaches to mitigate the effects of...
Frida Eng, Fredrik Gustafsson