Results 21 to 30 of about 8,467,026 (293)

Perfect posterior simulation for mixture and hidden Markov models [PDF]

, 2010
In this paper we present an application of the read-once coupling from the past algorithm to problems in Bayesian inference for latent statistical models.
Berthelsen, Kasper Klitgaard, Laird A. Breyer, Berthelsen, Kasper K., Kasper K. Berthelsen, Roberts, Gareth O., Breyer, Laird A., Gareth O. Roberts   +6 more
core   +1 more source

PDA-BCJR algorithm for factorial hidden Markov models with application to MIMO equalisation [PDF]

, 2006
In this paper we develop an efficient algorithm for inference in Factorial Hidden Markov Models (FHMM), which is particularly suitable for turbo equalisation in Multiple Input-Multiple Output (MIMO) systems.
Piechocki, Robert, McGeehan, Joe, Sandell, M, Andrieu, C., Piechocki, RJ, Sandell, Magnus, Andrieu, C, McGeehan, JP   +7 more
core   +1 more source

Performance of hidden Markov model and dynamic Bayesian network classifiers on handwritten Arabic word recognition [PDF]

, 2011
This paper presents a comparative study of two machine learning techniques for recognizing handwritten Arabic words, where hidden Markov models (HMMs) and dynamic Bayesian networks (DBNs) were evaluated.
Jinchang Ren, Alkhateeb, Jawad H., Jiang, J, Ren, J, Pauplin, Olivier, Alkhateeb, JH, Ren, Jinchang, Jawad H. AlKhateeb, Olivier Pauplin, Pauplin, O, Jiang, Jianmin, Jianmin Jiang   +11 more
core   +4 more sources

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
doaj   +1 more source

A Novel Method for Decoding Any High-Order Hidden Markov Model

Discrete Dynamics in Nature and Society, 2014
This paper proposes a novel method for decoding any high-order hidden Markov model. First, the high-order hidden Markov model is transformed into an equivalent first-order hidden Markov model by Hadar’s transformation. Next, the optimal state sequence of
Fei Ye, Yifei Wang
doaj   +1 more source

China's GDP forecasting using Long Short Term Memory Recurrent Neural Network and Hidden Markov Model.

PLoS ONE, 2022
This paper presents a Long Short Term Memory Recurrent Neural Network and Hidden Markov Model (LSTM-HMM) to predict China's Gross Domestic Product (GDP) fluctuation state within a rolling time window.
Junhuan Zhang, Jiaqi Wen, Zhen Yang
doaj   +2 more sources

Scoring hidden Markov models [PDF]

Bioinformatics, 1997
Statistical sequence comparison techniques, such as hidden Markov models and generalized profiles, calculate the probability that a sequence was generated by a given model. Log-odds scoring is a means of evaluating this probability by comparing it to a null hypothesis, usually a simpler statistical model intended to represent the universe of sequences ...
Christian Barrett, Richard Hughey, Kevin Karplus   +2 more
openaire   +3 more sources

Recognition of Warping Face Image and Morphing Face Image of Two Warping Image Using Hidden Markov Model [PDF]

المجلة العراقية للعلوم الاحصائية, 2011
In this paper, using algorithm models of Hidden Markov models, it has been concluded that the possibility of recognizing the warp face and the morph face the image real departments face on recognizing object.
doaj   +1 more source

Option pricing using hidden Markov models [PDF]

, 2006
Includes bibliographical references (leaves 144-149).This work will present an option pricing model that accommodates parameters that vary over time, whilst still retaining a closed-form expression for option prices: the Hidden Markov Option Pricing ...
Anderson, Michael
core   +1 more source

fHMM: Hidden Markov Models for Financial Time Series in R

Journal of Statistical Software
Hidden Markov models constitute a versatile class of statistical models for time series that are driven by hidden states. In financial applications, the hidden states can often be linked to market regimes such as bearish and bullish markets or ...
Lennart Oelschläger, Timo Adam, Rouven Michels   +2 more
doaj   +1 more source