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JMLR
2006
143views more  JMLR 2006»
13 years 8 months ago
Segmental Hidden Markov Models with Random Effects for Waveform Modeling
This paper proposes a general probabilistic framework for shape-based modeling and classification of waveform data. A segmental hidden Markov model (HMM) is used to characterize w...
Seyoung Kim, Padhraic Smyth
PE
2002
Springer
124views Optimization» more  PE 2002»
13 years 8 months ago
Continuous-time hidden Markov models for network performance evaluation
In this paper, we study the use of continuous-time hidden Markov models (CT-HMMs) for network protocol and application performance evaluation. We develop an algorithm to infer the...
Wei Wei, Bing Wang, Donald F. Towsley
MIAR
2010
IEEE
13 years 7 months ago
Hidden Markov Model for Quantifying Clinician Expertise in Flexible Instrument Manipulation
Clinicians are trained to manipulate a colonoscope while minimizing the force exerted on the colon walls to reduce the danger of luminal perforation and discomfort to the patient. ...
Jagadeesan Jayender, Raúl San José E...
CDC
2008
IEEE
157views Control Systems» more  CDC 2008»
13 years 9 months ago
A hidden Markov filtering approach to multiple change-point models
We describe a hidden Markov modeling approach to multiple change-points that has attractive computational and statistical properties. This approach yields explicit recursive filter...
Tze Leung Lai, Haipeng Xing
BMCBI
2008
170views more  BMCBI 2008»
13 years 9 months ago
Implementing EM and Viterbi algorithms for Hidden Markov Model in linear memory
Background: The Baum-Welch learning procedure for Hidden Markov Models (HMMs) provides a powerful tool for tailoring HMM topologies to data for use in knowledge discovery and clus...
Alexander G. Churbanov, Stephen Winters-Hilt