Homogeneous Continuous-Time, Finite-State Hidden Semi-Markov Modeling for Enhancing Empirical Classification System Diagnostics of Industrial Components

Hidden semi-Markov Model based earthquake classification system using Weighted Finite-State Transducers

Automatic earthquake detection and classification is required for efficient analysis of large seismic datasets. Such techniques are particularly important now because access to measures of ground motion is nearly unlimited and the target waveforms (earthquakes) are often hard to detect and classify. Here, we propose to use models from speech synthesis which extend the double stochastic models f...

Continuous-time homogeneous Markov chains

Optimal linear feature transformations for semi-continuous hidden Markov models

Linear discriminant or Karhunen-Lo eve transforms are established techniques for mapping features into a lower dimensional subspace. This paper introduces a uniform statistical framework, where the computation of the optimal feature reduction is formalized as a Maximum-Likelihood estimation problem. The experimental evaluation of this suggested extension of linear selection methods shows a slig...

Finite State Transducers Approximating Hidden Markov Models

This paper describes the conversion of a Hidden Markov Model into a sequential transducer that closely approximates the behavior of the stochastic model. This transformation is especially advantageous for part-of-speech tagging because the resulting transducer can be composed with other transducers that encode correction rules for the most frequent tagging errors. The speed of tagging is also i...

Discrete Time Homogeneous and non-Homogeneous semi-Markov Reliability Models.∗

In this paper, we extend to our knowledge, for the first case, some reliability results obtained using homogeneous semi-Markov processes to the case of non-homogenous semi-Markov modelisation. Moreover, we apply some of our preceding results to give the numerical solutions and so the possibility to treat real life problems for which non-homogeneity in time is important.