Hidden Markov Models
Identification of plasmodium vivax proteins with potential role in invasion using sequence redundancy reduction and profile hidden markov models
... Hidden Markov models (HMMs) are among the most effective and efficient approaches for analyzing large sets of biological data ...These models have been applied over the last 20 years in ...
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Hidden Markov models in dissimilarity spaces: alternatives for prototype selection
... involving hidden Markov models employs maximum likelihood rule for the election of the correct ...between hidden Markov models improves the system’s ...using hidden ...
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EM Training of Hidden Markov Models for Shape Recognition Using Cyclic Strings
... Dynamic Time Warping (DTW) is being increasingly applied for shape match- ing [1]. A DTW-based dissimilarity measure is a natural option for optimally aligning contours, since it is able to align parts as well as points ...
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Definition and composition of motor Primitives using latent force models and hidden markov models
... In this section we describe the foundations required to introduce the proposed probabilistic model as well as one of the previous motor primitive definitions which motivated this work. Firstly, we present the dynamical ...
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Estimación de actividad de trabajadores hospitalarios con modelos ocultos de MarkovEstimating hospital workers activities using hidden markov models
... Finalmente, los resultados de las estimaciones de actividad con el modelo en paralelo en dos capas mejoraron notablemente (92.6%), comparado con los resultados de las estimaciones de actividad utilizando redes neuronales ...
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A Gaussian Mixture Model Hidden Markov Model (GMM HMM) based fiber optic surveillance system for pipeline integrity threat detection
... Mixture Models-Hidden Markov Models (GMMs- HMMs) that operates in two modes: 1) The machine+activity identification mode classifies different activities occurring in different locations along ...
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A Statistical LearningPattern Recognition Glossary
... Grouping similar objects in a multidimensional space. It is useful for constructing new features which are abstractions of the existing features. Some algorithms, like k-means, simply partition the feature space. Other ...
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Pattern recognition glossary pdf
... Grouping similar objects in a multidimensional space. It is useful for constructing new features which are abstractions of the existing features. Some algorithms, like k-means, simply partition the feature space. Other ...
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Design of a real-time hidden markov model state decoding system
... - Hidden Markov Models are used in different kinds of sequence recognition ...Specially, Hidden Markov Models are suited for speech/speaker recognition ...using Hidden ...
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BRAIN COMPUTER INTERFACE - Application of an Adaptive Bi-stage Classifier based on RBF-HMM
... Abstract: Brain Computer Interface is an emerging technology that allows new output paths to communicate the user’s intentions without the use of normal output paths, such as muscles or nerves. In order to obtain their ...
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Combination of Standard and Complementary Models for Audio-Visual Speech Recognition
... Abstract. In this work, new multi-classifier schemes for isolated word speech recognition based on the combination of standard Hidden Markov Models (HMMs) and Complementary Gaussian Mixture ...
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Stochastic approach to determine spatial patterns of lizard community on a desert island
... ecology, Markov chains have been used principally in temporal succession of ecological states (Tanner et ...2003). Markov chains spatial models have been used to predict sequences of egg- laying in ...
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Uso de las cadenas de Markov para un modelo de negocios
... Abstract: Predicting the sales of a product from an industry is a significant mathematical problem for business, mainly in the production of aloe as raw material, the bosses, poor optimization processes and other factors ...
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Critical Analysis of Markov Models Used for the Economic Evaluation of Colorectal Cancer Screening: A Systematic Review
... available Markov models and to critically analyze their main structural ...34 models that met the inclusion ...a Markov model to reproduce the natural history of the disease and an overlaying ...
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PROBLEMAS RESUELTOS DE CADENAS DE MARKOV TEMA: CADENAS DE MARKOV
... de Markov incluyendo tres estados, los estados G y H representan a los clientes que beben cerveza producida por las mencionadas cervecerías y el estado I representa todas las demás ...
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Dynamic programming for variable discounted Markov decision problems
... With this new way of defining the value of a policy, we show existence of Markov deterministic optimal policies in the finite-horizon case, and a recursive method to obtain such ones. For the infinite horizon ...
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UPGMpp: a Software Library for Contextual Object Recognition
... Graphical Models in C++ (UPGMpp) library, a software package for working with undirected PGMs, as is the case of CRFs, and its application to scene object ...
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CADENAS DE MARKOV parte 2
... Daniel, director de Gestión Humana sabe que los cambios de personal pueden ser modelados matemáticamente como cadenas de Markov. Revisando los registros dela empresa pudo establecer la matriz de transición más ...
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Venegas Barrera et al , 2008
... of Markov chains are that: (1) such models are relatively easy to derive from continuous data; (2) the model does not require deep insight into the mechanisms of dynamic change; (3) the basic transition ...
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An adaptive reading tutor using Markov models to develop phonological awareness
... An intelligent tutor that, at a general level, is similar to the one developed and tested as part of the present work was described by Cassandra in 1998 as a possible application of POMDP models to education ...
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