Results 271 to 280 of about 60,493 (305)
Some of the next articles are maybe not open access.
Hidden Markov Models in Biology
2009Markov and Hidden Markov models (HMMs) are introduced using examples from linkage mapping and sequence analysis. In the course, the forward-backward, the Viterbi, the Baum-Welch (EM) algorithm, and a Metropolis sampling scheme are presented.
Vogl, Claus, Futschik, Andreas
openaire +3 more sources
A modified hidden Markov model
Automatica, 2013This paper considers two discrete time, finite state processes X and Y. In the usual hidden Markov model X modulates the values of Y. However, the values of Y are then i.i.d. given X. In this paper a new model is considered where the Markov chain X modulates the transition probabilities of the second, observed chain Y.
John van der Hoek, Robert J. Elliott
openaire +2 more sources
Modelling stabilograms with hidden Markov models
Journal of Medical Engineering & Technology, 2008Hidden Markov models are an effective computational method for modelling and interpreting digital signals of biological, as well as other, origin. In the current investigation, we explored whether hidden Markov models can be used to control and represent phenomena in human balance signals recorded from subjects standing on a force platform ...
J, Rasku +4 more
openaire +2 more sources
On the Learnability of Hidden Markov Models
2002A simple result is presented that links the learning of hidden Markov models to results in complexity theory about nonlearnability of finite automata under certain cryptographic assumptions. Rather than considering all probability distributions, or even just certain specific ones, the learning of a hidden Markov model takes place under a distribution ...
openaire +2 more sources
Hidden Markov Models with Confidence
2016We consider the problem of training a Hidden Markov Model HMM from fully observable data and predicting the hidden states of an observed sequence. Our attention is focused to applications that require a list of potential sequences as a prediction. We propose a novel method based on Conformal Prediction CP that, for an arbitrary confidence level $$1 ...
Giovanni Cherubin, Ilia Nouretdinov
openaire +1 more source
Evolving the structure of hidden Markov models
IEEE Transactions on Evolutionary Computation, 2006A genetic algorithm (GA) is proposed for finding the structure of hidden Markov Models (HMMs) used for biological sequence analysis. The GA is designed to preserve biologically meaningful building blocks. The search through the space of HMM structures is combined with optimization of the emission and transition probabilities using the classic Baum ...
Kyoung-Jae Won +2 more
openaire +3 more sources
Hidden Markov models and steganalysis
Proceedings of the 2004 workshop on Multimedia and security, 2004In this paper we presented a novel approach to steganalysis. We formulated two problems for steganalysis and showed that these problems can be solved using the theory of hidden markov models, the case of LSB encoding is discussed in detail. Some suggestions about steganalysis of images using hidden markov field model conclude the paper.
openaire +1 more source
Partially exchangeable Hidden Markov Models
2009 European Control Conference (ECC), 2009Hidden Markov Models (HMMs) have become increasingly popular in recent years in a wide range of applications. Special subclasses of HMMs have been extensively studied in various contexts. In this work we give a necessary and sufficient condition for a partially exchangeable sequence to be a countable HMM, i.e.
Finesso L, Prosdocimi C
openaire +3 more sources
Proceedings of the International Conference & Workshop on Emerging Trends in Technology - ICWET '11, 2011
This paper focuses on concept of Hidden Markov Model and its practical applications, with the detailed description of HMM based algorithms used in Named Entity Recognition. This paper is comprised of 9 sections. Section 1 provides brief introduction about Hidden Markov Model, Section 2 describes HMM in detail by making use of a practical problem ...
openaire +1 more source
This paper focuses on concept of Hidden Markov Model and its practical applications, with the detailed description of HMM based algorithms used in Named Entity Recognition. This paper is comprised of 9 sections. Section 1 provides brief introduction about Hidden Markov Model, Section 2 describes HMM in detail by making use of a practical problem ...
openaire +1 more source
Substitution Matrices and Hidden Markov Models
Journal of Computational Biology, 1995Hidden Markov models (HMMs) provide a general framework for expressing primary sequence consensus. HMMs can effectively be used to model and align protein families, and to search data bases. HMMs, however, have a large number of parameters. When only few sequences are available for model fitting, additional prior information must be incorporated into ...
openaire +2 more sources