Results 1 to 10 of about 7,474,817 (334)
Feature Selection for Hidden Markov Models and Hidden Semi-Markov Models
IEEE Access, 2016 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
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Network motif detection using hidden markov models [PDF]
Scientific ReportsGraphical representations model complex networks by encoding entities as vertices and interactions as edges, with recurring subgraphs—or motifs—revealing fundamental organizational principles. We present a novel application of Hidden Markov Models (HMMs)
Costas Bampos, Vasileios Megalooikonomou
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Incorporating sparse labels into hidden Markov models using weighted likelihoods improves accuracy and interpretability in biologging studies. [PDF]
PLoS ONEEcologists often use a hidden Markov model to decode a latent process, such as a sequence of an animal's behaviours, from an observed biologging time series.
Evan Sidrow +6 more
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Validating hidden Markov models for seabird behavioural inference [PDF]
Ecology and EvolutionUnderstanding animal movement and behaviour can aid spatial planning and inform conservation management. However, it is difficult to directly observe behaviours in remote and hostile terrain such as the marine environment. Different underlying states can
Rebecca A. Akeresola +6 more
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International Clinical Neuroscience Journal, 2022 Background: In this study, three detecting approaches have been proposed and evaluated for online detection of balance situations during quiet standing.
Rashin Abdolhossein Harisi +1 more
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Uncovering ecological state dynamics with hidden Markov models [PDF]
Ecology Letters, 2020 Ecological systems can often be characterised by changes among a finite set of underlying states pertaining to individuals, populations, communities or entire ecosystems through time.
B. McClintock +6 more
semanticscholar +1 more source
Hidden Markov models: Pitfalls and opportunities in ecology
Methods in Ecology and Evolution, 2022 Hidden Markov models (HMMs) and their extensions are attractive methods for analysing ecological data where noisy, multivariate measurements are made of a hidden, ecological process, and where this hidden process is represented by a sequence of discrete ...
Richard Glennie +5 more
semanticscholar +1 more source
Factorial Hidden Markov Models [PDF]
Machine Learning, 1996 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zoubin Ghahramani, Michael I. Jordan
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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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Improving the Recognition Rate of Phonetic Arabic Letters Via Artificial Intelligent [PDF]
The Egyptian International Journal of Engineering Sciences and Technology, 2020 It is very important to enhance the recognition accuracy of the Arabic spoken letters. The accuracy of recognition system is affected by the feature extraction and the used classifier. An effective and robust method is proposed to evaluate speech feature
I Zedan, E Mohamed, Z Aly
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