Results 31 to 40 of about 5,911 (187)
Artificial Intelligence, 2010 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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SMCis: An Effective Algorithm for Discovery of Cis-Regulatory Modules. [PDF]
PLoS ONE, 2016 The discovery of cis-regulatory modules (CRMs) is a challenging problem in computational biology. Limited by the difficulty of using an HMM to model dependent features in transcriptional regulatory sequences (TRSs), the probabilistic modeling methods ...
Haitao Guo, Hongwei Huo, Qiang Yu
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Protein secondary structure prediction for a single-sequence using hidden semi-Markov models
BMC Bioinformatics, 2006 Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about ...
Borodovsky Mark +2 more
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Global discriminative learning for higher-accuracy computational gene prediction. [PDF]
PLoS Computational Biology, 2007 Most ab initio gene predictors use a probabilistic sequence model, typically a hidden Markov model, to combine separately trained models of genomic signals and content.
Axel Bernal +3 more
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Introduction to Hidden Semi-Markov Models
, 2018 The purpose of this volume is to present the theory of Markov and semi-Markov processes in a discrete-time, finite-state framework. Given this background, hidden versions of these processes are introduced and related estimation and filtering results developed. The approach is similar to the earlier book, Elliott et al. (1995).
John van der Hoek, Robert J. Elliott
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Bayesian Nonparametric Hidden Semi-Markov Models
, 2012 There is much interest in the Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) as a natural Bayesian nonparametric extension of the ubiquitous Hidden Markov Model for learning from sequential and time-series data. However, in many settings the HDP-HMM's strict Markovian constraints are undesirable, particularly if we wish to learn or encode
Johnson, Matthew James, Willsky, Alan S.
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MathematicsRegime switching models have been widely studied for their ability to capture the dynamic behavior of time series data and are widely used in economic and financial data analysis.
Zhenni Tan, Yuehua Wu
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Log-Viterbi algorithm applied on second-order hidden Markov model for human activity recognition
International Journal of Distributed Sensor Networks, 2018 Recognition of human activities is getting into the limelight among researchers in the field of pervasive computing, ambient intelligence, robotic, and monitoring such as assistive living, elderly care, and health care.
Yang Sung-Hyun +3 more
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Advanced Intelligent Systems, EarlyView.This study introduces a data‐driven framework that combines deep reinforcement learning with classical path planning to achieve adaptive microrobot navigation. By training a surrogate neural network to emulate microrobot dynamics, the approach improves learning efficiency, reduces training time, and enables robust real‐time obstacle avoidance in ...
Amar Salehi +3 more
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Peer Community JournalState-space models are widely used in ecology to infer hidden behaviors. This study develops an extensive numerical simulation-estimation experiment to evaluate the state decoding accuracy of four simple state-space models.
Bez, Nicolas +8 more
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