Results 241 to 250 of about 101,818 (290)

4Approximate realization of hidden Markov chains

Proceedings of the IEEE Information Theory Workshop, 2003
In this paper we consider the approximate realization problem for finite valued hidden Markov models i.e. stochastic processes Y=f(X) where X is a finite state Markov chain and f a many-to-one function. Given the laws p/sub Y/(/spl middot/) of Y the weak realization problem consists in finding a Markov chain X and a function f such that, at least ...
L. Finesso, P. Spreij
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Parameter estimation for hidden Markov chains

Journal of Statistical Planning and Inference, 2002
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Archer, G. E. B., Titterington, D. M.
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Hidden markov chain identification

IEEE Workshop on Statistical Signal Processing, 2003, 2004
An identification scheme is developed for hidden Markov models (HMM). Unlike the realization problem, where one starts from exact probabilities, the identification problem makes a statistical inference from the pathwise output sequences. The basic principle in the identification of Markovian finite state systems from nonnumeric inputs and outputs is ...
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On White Noises Driven by Hidden Markov Chains

Journal of Time Series Analysis, 1997
We consider a time series model where the variance of the underlying process depends on the state of a non‐observed Markov chain. Maximum likelihood estimates are shown to be consistent. Estimators with asymptotic Gaussian distribution are proposed. Prediction and identification are also mentioned.
Francq, Christian, Roussignol, Michel
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Hidden Markov chain modeling for epileptic networks identification

2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2013
The partial epileptic seizures are often considered to be caused by a wrong balance between inhibitory and excitatory interneuron connections within a focal brain area. These abnormal balances are likely to result in loss of functional connectivities between remote brain structures, while functional connectivities within the incriminated zone are ...
Le Cam, Steven, Louis-Dorr, Valérie, Maillard, Louis   +2 more
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Computational methods for discrete hidden semi‐Markov chains

Applied Stochastic Models in Business and Industry, 1999
Hidden Markov chains emerged in the 1970s in engineering and have since become a major tool for both pattern recognition applications such as speech or handwriting recognition or biological sequence analysis. Semi-Markov processes (or Markov renewal processes) have been applied for a long time in such diverse fields as biostatistics, operations ...
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Markov Chains and Hidden Markov Models

2017
There are many situations where one must work with sequences. Here is a simple, and classical, example. We see a sequence of words, but the last word is missing. I will use the sequence “I had a glass of red wine with my grilled xxxx”. What is the best guess for the missing word?
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Unsupervised classification of radar images using hidden Markov chains and hidden Markov random fields

IEEE Transactions on Geoscience and Remote Sensing, 2003
Due to the enormous quantity of radar images acquired by satellites and through shuttle missions, there is an evident need for efficient automatic analysis tools. This paper describes unsupervised classification of radar images in the framework of hidden Markov models and generalized mixture estimation.
R. Fjortoft, Y. Delignon, W. Pieczynski, M. Sigelle, F. Tupin   +4 more
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Neural Network Generating Hidden Markov Chain

2005
In this paper we introduce technique how a neural network can generate a Hidden Markov Chain. We use neural network called Temporal Information Categorizing and Learning Map. The network is an enhanced version of standard Categorizing and Learning Module (CALM).
J. Koutník, M. Šnorek
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Markov chain existence and Hidden Markov models in spectrum sensing

2009 IEEE International Conference on Pervasive Computing and Communications, 2009
The primary function of a cognitive radio is to detect idle frequencies or sub-bands, not used by the primary users (PUs), and allocate these frequencies to secondary users. The state of the sub-band at any time point is either free (unoccupied by a PU) or busy (occupied by a PU).
Chittabrata Ghosh, Carlos Cordeiro, Dharma P. Agrawal, M. Bhaskara Rao   +3 more
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