Results 21 to 30 of about 203,293 (263)
Hidden Markov models: the best models for forager movements? [PDF]
PLoS ONE, 2013 One major challenge in the emerging field of movement ecology is the inference of behavioural modes from movement patterns. This has been mainly addressed through Hidden Markov models (HMMs).
Rocio Joo +3 more
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Supply Sequence Modelling Using Hidden Markov Models
Applied Sciences, 2022 Logistics processes, their effective planning as well as proper management and effective implementation are of key importance in an enterprise. This article analyzes the process of supplying raw materials necessary for the implementation of production ...
Anna Borucka +5 more
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EURASIP Journal on Audio, Speech, and Music Processing, 2010 Speaker identification performance is almost perfect in neutral talking environments. However, the performance is deteriorated significantly in shouted talking environments.
Ismail Shahin
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Analysis and Comparison of Bitcoin and S and P 500 Market Features Using HMMs and HSMMs †
Information, 2019 We implement hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) on Bitcoin/US dollar (BTC/USD) with the aim of market phase detection. We make analogous comparisons to Standard and Poor’s 500 (S and P 500), a benchmark traditional ...
David Suda, Luke Spiteri
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Using multiple visual tandem streams in audio-visual speech recognition [PDF]
, 2011 The method which is called the "tandem approach" in speech recognition has been shown to increase performance by using classifier posterior probabilities as observations in a hidden Markov model.
Erdogan, Hakan +3 more
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A Novel Method for Decoding Any High-Order Hidden Markov Model
Discrete Dynamics in Nature and Society, 2014 This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of
Fei Ye, Yifei Wang
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Unsupervised Neural Hidden Markov Models [PDF]
, 2016 In this work, we present the first results for neuralizing an Unsupervised Hidden Markov Model. We evaluate our approach on tag in- duction. Our approach outperforms existing generative models and is competitive with the state-of-the-art though with a ...
Bisk, Yonatan +4 more
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Strong and Weak Optimizations in Classical and Quantum Models of Stochastic Processes [PDF]
, 2018 Among the predictive hidden Markov models that describe a given stochastic process, the {\epsilon}-machine is strongly minimal in that it minimizes every R\'enyi-based memory measure. Quantum models can be smaller still.
Crutchfield, James P., Loomis, Samuel
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Real-Time Assembly Support System with Hidden Markov Model and Hybrid Extensions
Mathematics, 2022 This paper presents a context-aware adaptive assembly assistance system meant to support factory workers by embedding predictive capabilities. The research is focused on the predictor which suggests the next assembly step.
Arpad Gellert +4 more
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fHMM: Hidden Markov Models for Financial Time Series in R
Journal of Statistical SoftwareHidden Markov models constitute a versatile class of statistical models for time series that are driven by hidden states. In financial applications, the hidden states can often be linked to market regimes such as bearish and bullish markets or ...
Lennart Oelschläger +2 more
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