Gaussian model-based approach
A Bayesian Approach to Inference and Prediction for Spatially Correlated Count Data Based on Gaussian Copula Model
... completely model the high-dimensional ...our approach yields better and more consistent results than the existing method and that our approach can significantly decrease computational burden, in the ...
8
Model based clustering of non Gaussian panel data
... As the aims of this paper are rather similar to those of Frühwirth-Schnatter and Kaufmann (2004), we briefly highlight the differences with the approach used in that paper. Firstly, our modelling allows for ...
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Discriminative Shared Gaussian Process Based On Latent Variable Model An Approach for Facial Expression Recognition
... shared Gaussian process latent variable model (DS-GPLVM) for multi-view and view- invariant separation of facial expressions from multiple views ...this model, first learn a discriminative manifold ...
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Phase Based Binarization with Gaussian Summation Model for Ancient Documents
... andmethodsoftimeseriesprocessingmaybeusedtoextracttheunderlyingcharacteristics.Asapreprocessingstep, the textstreamissplitinto shortwindows,andfrom eachwindowaT-dimensional vectorisformed,whereTis ...
7
Moving Object Detection using Temporal Information in Surveillance System using Matlab and ARM7 Processor
... designed based on temporal information, such as frame difference [2][3] and background subtraction ...background model from the input images. This is most common approach to detect moving ...Mixture ...
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Modeling International Financial Returns with a Multivariate Regime Switching Copula
... copula model for the dependence of the stock indices of the G5 and of four Latin American ...to model the dependence in a much more flexible and realistic way than switching models based on the ...
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A Physiologically Based Adaptive Three Gaussian Function Model for Image Enhancement
... physiologically based adaptive three-Gaussian model, which dynami- cally adjusts the parameters of the three-Gaussian ...new model is better than the standard three-Gaussian ...
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A Novel Feature Extraction Techniques for Multimodal Score Fusion Using Density Based Gaussian Mixture Model Approach
... B. Transformation-based score fusion: Accurate estimation of the class conditional densities is possible only when the number of match scores available for training the fusion module is large. When the number of ...
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A Unifying Probabilistic Perspective for Spectral Dimensionality Reduction: Insights and New Models
... as Gaussian Markov random fields (GRFs). Our unifying perspective is based on the maximum entropy principle which is in turn inspired by maximum variance ...resulting model, which we call maximum ...
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Speech based Emotion Recognition with Gaussian Mixture Model
... processing approach suffers from some logical problems, they are: physical blocking of speech signal may not be suitable for extracting features, as it is difficult to find relationships among the neighboring ...
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An Efficient Time-Varying Filter for Detrending and Bandwidth Limiting the Heart Rate Variability Tachogram without Resampling: MATLAB Open-Source Code and Internet Web-Based Implementation
... Copyright © 2012 A. Eleuteri et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the ...
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A Multi Model Based Bio Metric Analysis Using Gaussian Distribution
... authentication approach fusing palm print and fingerprint traits at ...multi model authentication, Generalized Gaussian distribution is used on the features of both the prints which are further used ...
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Gaussian Mixture Model based Spatial Information Concept for Image Segmentation
... To illustrate the computational cost of this approach, an image (245x245 image resolution) with three labels as shown in Figure 3.2(a) is used. The im- age shown in Figure 3.2(b) is made from the original image by ...
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Pseudo-measurement simulations and bootstrap for the experimental cross-section covariances estimation with quality quantification
... statistical approach for the covariances evaluation based on the generation of gaussian pseudo-measurements around a regression model which is assimilated to the ...this approach is ...
5
Efficient Gaussian Process Classification Using Pólya-Gamma Data Augmentation
... inference approach (cf. section 4) to the plain P´olya- Gamma augmented model (5) leads to the same bound for GP classification derived by Gibbs and MacKay ...augmentation approach. We pro- vide a ...
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Contaminant Source Identification in Water Distribution Networks under the conditions of Uncertainty
... Water distribution systems are vulnerable to deliberate biological or chemical contamination into the system and have adverse health and safety impacts on the consumers. On the other hand, the values of demands at ...
60
Comparative Analysis of Resource Discovery Approaches in Grid Computing
... swamping Approach [13] for message ...universal Approach is more expensive in terms of message complexity than that of neighborhood and distinctive ...
5
Incorporating covariates in skewed functional data models
... in model (1) leads to an increased dimensionality of the problem, and thus demands for computationally feasible ...to model the residuals; Jiang and Wang (2010) introduce a modification of the existing FPCA ...
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Adaptation of Maximum Entropy Capitalizer: Little Data Can Help a Lo
... MEMM model param- eters using MAP smoothing builds on the Gaussian prior model used for smoothing MaxEnt models, as presented in (Chen and Rosenfeld, ...
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Properties And Experimental Of Gaussian And Non Gaussian Time Series Model
... with Gaussian and non Gaussian mixed ...forecasting model that best fits the data ...series model which can be used for simulating stationary river flow sequences with high skewness and the ...
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