Results 11 to 20 of about 65,576 (217)
Bayesian Nonparametric Hidden Semi-Markov Models
There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data.
Johnson, Matthew J., Willsky, Alan S.
core +2 more sources
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
In this paper, a joint feature selection and parameter estimation algorithm is presented for hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs).
Stephen Adams +2 more
doaj +2 more sources
Decoding Chinese stock market returns: three-state hidden semi-Markov model [PDF]
In this paper, we employ a three-state hidden semi-Markov model (HSMM) to explain the time-varying distribution of the Chinese stock market returns since 2005.
Liu, Zhenya, Wang, Shixuan
core +8 more sources
The Hierarchical Dirichlet Process Hidden Semi-Markov Model [PDF]
There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the traditional HMM.
Johnson, Matthew James, Willsky, Alan S
core +4 more sources
biomvRhsmm: genomic segmentation with hidden semi-Markov model. [PDF]
High-throughput technologies like tiling array and next-generation sequencing (NGS) generate continuous homogeneous segments or signal peaks in the genome that represent transcripts and transcript variants (transcript mapping and quantification), regions of deletion and amplification (copy number variation), or regions characterized by particular ...
Du Y, Murani E, Ponsuksili S, Wimmers K.
europepmc +5 more sources
A hidden semi-Markov model for estimating burst suppression EEG. [PDF]
Burst suppression is an electroencephalogram (EEG) pattern associated with profoundly inactivated brain states characterized by cerebral metabolic depression. This pattern is distinguished by short-duration band-limited electrical activity (bursts) interspersed between relatively near-isoelectric periods (suppressions).
Chakravarty S +4 more
europepmc +6 more sources
Heavy tailed hidden semi-markov models [PDF]
Summary: Hidden semi-Markov models have been proposed by \textit{K. S. Meier-Hellstern}, \textit{P. E. Wirth}, \textit{Y. L. Yan} and \textit{D. A. Hoeflin} [in: Teletraffic and datatraffic in a period of change (A. Jensen and V. B. Iversen (eds.)), 167-192 (1991)] to model the times between transmission of packets at a source.
Resnick, Sidney, Subramanian, Ajay
openaire +1 more source
Hidden Semi-Markov Models for Predictive Maintenance [PDF]
Realistic predictive maintenance approaches are essential for condition monitoring and predictive maintenance of industrial machines. In this work, we propose Hidden Semi-Markov Models (HSMMs) with (i) no constraints on the state duration density function and (ii) being applied to continuous or discrete observation. To deal with such a type of HSMM, we
Francesco Cartella +3 more
openaire +3 more sources
Use of Automation Technologies and Data Mining in Speech Recognition for Autism. [PDF]
Pipeline analyzes clinical and naturalistic speech using LENA, wav2vec 2.0, and foundation‐model ASR (Whisper) to enable scalable ASD detection and severity estimation. Future work integrates benchmarking, privacy‐preserving collaboration (federated learning), and explainable, edge‐ready AI for clinically credible assessment and longitudinal monitoring.
Mao R, Zhu Y.
europepmc +2 more sources
Hidden Markov Model and States Prediction of an Autonomous Wind-Diesel Complex [PDF]
The problem of assessing the reliability and analyzing the functioning of an autonomous winddiesel complex, consisting of a wind power plant, working and standby diesel generators, an inverter and a storage battery, is considered.
Obzherin Yuriy E. +2 more
doaj +1 more source

