Results 21 to 30 of about 42,871 (261)
ToPS: a framework to manipulate probabilistic models of sequence data. [PDF]
PLoS Computational Biology, 2013 Discrete Markovian models can be used to characterize patterns in sequences of values and have many applications in biological sequence analysis, including gene prediction, CpG island detection, alignment, and protein profiling.
André Yoshiaki Kashiwabara +5 more
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An Introduction to Hidden Markov Models [PDF]
Current Protocols in Bioinformatics, 2007 AbstractThis unit introduces the concept of hidden Markov models in computational biology. It describes them using simple biological examples, requiring as little mathematical knowledge as possible. The unit also presents a brief history of hidden Markov models and an overview of their current applications before concluding with a discussion of their ...
Schuster-Böckler, B, Bateman, A
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Hidden Markov Models with Momentum
CoRR, 2022 Momentum is a popular technique for improving convergence rates during gradient descent. In this research, we experiment with adding momentum to the Baum-Welch expectation-maximization algorithm for training Hidden Markov Models. We compare discrete Hidden Markov Models trained with and without momentum on English text and malware opcode data.
Andrew Miller +2 more
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Frontiers in Ecology and Evolution, 2021 The study of animal behavioral states inferred through hidden Markov models and similar state switching models has seen a significant increase in popularity in recent years.
Giada Sacchi, Ben Swallow
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Journal of Artificial Intelligence Research, 2006 Logical hidden Markov models (LOHMMs) upgrade traditional hidden Markov models to deal with sequences of structured symbols in the form of logical atoms, rather than flat characters. This note formally introduces LOHMMs and presents solutions to the three central inference problems for LOHMMs: evaluation, most likely hidden state sequence and ...
Kersting, K., De Raedt, Luc, Raiko, T.
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SOLUTION TO EVALUATION PROBLEM OF HIDDEN SEMI-MARKOV QP-MODELS
Advanced Engineering Research, 2014 A hidden semi-Markov QP-model is considered; and the way it could be embedded in a general hidden semi-Markov model is shown. The estimation problem (the first of three classical theory problems of the hidden Markov models and hidden semi-Markov models ...
V. M. Deundyak, M. A. Zhdanova
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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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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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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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