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Cluster adaptive training of hidden Markov models
IEEE Transactions on Speech and Audio Processing, 2000When performing speaker adaptation, there are two conflicting requirements. First, the speaker transform must be powerful enough to represent the speaker. Second, the transform must be quickly and easily estimated for any particular speaker. The most popular adaptation schemes have used many parameters to adapt the models to be representative of an ...
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Clustering of Bursts of Openings in Markov and Semi-Markov Models of Single Channel Gating
Advances in Applied Probability, 1997The gating mechanism of a single ion channel is usually modelled by a continuous-time Markov chain with a finite state space. The state space is partitioned into two classes, termed ‘open’ and ‘closed’, and it is possible to observe only which class the process is in. In many experiments channel openings occur in bursts.
Ball, Frank, Davies, Sue
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Deep Markov Clustering for Panoptic Segmentation
ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022Minxiang Ye +4 more
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Asynchronous Fault Detection Observer for 2-D Markov Jump Systems
IEEE Transactions on Cybernetics, 2022Peng Cheng +2 more
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Clustering Multivariate Longitudinal Data: Hidden Markov of Factor Analyzers
2012Parsimonious Hidden Markov of Factor Analyzers models are developedby using a modified factor analysis covariance structure. This framework can be seenas a extension of the Parsimonious Gaussian mixture models (PGMMs) accountingfor heterogeneity in a longitudinal setting.
MARTELLA, Francesca, A. Maruotti
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Markov Decision Processes With Applications in Wireless Sensor Networks: A Survey
IEEE Communications Surveys and Tutorials, 2015Mohammad Abu Alsheikh +2 more
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