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Hidden Markov Models for the Prediction of Impending Faults
IEEE transactions on industrial electronics (1982. Print), 2016Reliability and safety are two important concepts in industrial applications. Thus, the development of monitoring tools, which are able to ensure the continuity of service by predicting faults, should improve competitiveness.
A. Soualhi +4 more
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2017
Die Grundlagen der Hidden-Markov-Modelle (HMM) werden in diesem Kapitel behandelt. Dazu gehoren insbesondere die Algorithmen, welche die grundlegenden Probleme der HMM losen: Forward-Algorithmus, Viterbi-Algorithmus und Baum-Welch-Algorithmus. Das Trellis-Diagramm wird eingesetzt um diese Algorithmen anschaulich zu erklaren.
Beat Pfister, Tobias Kaufmann
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Die Grundlagen der Hidden-Markov-Modelle (HMM) werden in diesem Kapitel behandelt. Dazu gehoren insbesondere die Algorithmen, welche die grundlegenden Probleme der HMM losen: Forward-Algorithmus, Viterbi-Algorithmus und Baum-Welch-Algorithmus. Das Trellis-Diagramm wird eingesetzt um diese Algorithmen anschaulich zu erklaren.
Beat Pfister, Tobias Kaufmann
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2014
In the field of pattern recognition, signals are frequently thought of as the product of a statistical generation process. The primary goal of analyzing these signals is to model their statistical properties as exactly as possible. However, the model to be determined should not only replicate the generation of certain data but also deliver useful ...
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In the field of pattern recognition, signals are frequently thought of as the product of a statistical generation process. The primary goal of analyzing these signals is to model their statistical properties as exactly as possible. However, the model to be determined should not only replicate the generation of certain data but also deliver useful ...
openaire +1 more source
2003
Im Bereich der Mustererkennung betrachtet man Signale haufig als das Produkt statistisch agierender Quellen. Das Ziel der Signalanalyse ist es daher, die statistischen Eigenschaften dieser angenommenen Signalquellen moglichst genau zu modellieren. Als Basis der Modellbildung stehen dabei lediglich die beobachteten Beispieldaten sowie einschrankende ...
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Im Bereich der Mustererkennung betrachtet man Signale haufig als das Produkt statistisch agierender Quellen. Das Ziel der Signalanalyse ist es daher, die statistischen Eigenschaften dieser angenommenen Signalquellen moglichst genau zu modellieren. Als Basis der Modellbildung stehen dabei lediglich die beobachteten Beispieldaten sowie einschrankende ...
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A tutorial on hidden Markov models and selected applications in speech recognition
Proceedings of the IEEE, 1989L. Rabiner
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An introduction to hidden Markov models
IEEE ASSP Magazine, 1986L. Rabiner, B. Juang
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Wavelet-based statistical signal processing using hidden Markov models
IEEE Transactions on Signal Processing, 1998M. Crouse, R. Nowak, Richard Baraniuk
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2015
Markov chains and hidden Markov models (HMMs) are particular types of PGMs that represent dynamic processes. After a brief introduction to Markov chains, this chapter focuses on hidden Markov models. The algorithms for solving the basic problems: evaluation, optimal sequence, and parameter learning are presented.
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Markov chains and hidden Markov models (HMMs) are particular types of PGMs that represent dynamic processes. After a brief introduction to Markov chains, this chapter focuses on hidden Markov models. The algorithms for solving the basic problems: evaluation, optimal sequence, and parameter learning are presented.
openaire +1 more source