نتایج جستجو برای: gaussian model
تعداد نتایج: 2151828 فیلتر نتایج به سال:
The Dirichlet process is a prior used in nonparametric Bayesian models of data, particularly in Dirichlet process mixture models (also known as infinite mixture models). It is a distribution over distributions, i.e. each draw from a Dirichlet process is itself a distribution. It is called a Dirichlet process because it has Dirichlet distributed finite dimensional marginal distributions, just as...
We develop multivariate copulas for modeling multiple joint distributions of wind speeds at a wind farm site and neighboring wind source. A ndimensional Gaussian copula and multiple copula graphical models enhance the quality of the prediction site distribution. The models, in comparison to multiple regression, achieve higher accuracy and lower cost because they require less sensing data.
In this paper an estimator of speech spectrum for speech enhancement based on Laplacian Mixture Model has been proposed. We present an analytical solution for estimating the complex DFT coefficients with the MMSE estimator when the clean speech DFT coefficients are mixture of Laplacians distributed. The distribution of the DFT coefficients of noise are assumed zero-mean Gaussian.The drived MMSE...
The feedback capacity of the stationary Gaussian additive noise channel has been open, except for the case where the noise is white. Here we obtain the closed-form feedback capacity of the first-order moving average additive Gaussian noise channel. Specifically, the channel is given by Yi = Xi +Zi, i = 1, 2, . . . , where the input {Xi} satisfies a power constraint and the noise {Zi} is a first...
In this paper, Gaussian Process Regression (GPR)-based models which use the Bayesian approach to regression analysis problem such as load forecasting (LF) are proposed. The GPR is a non-parametric kernel-based learning method having ability provide correct predictions with uncertainty in measurements. proposed model provides an hourly and monthly forecast for Australian city four Indian cities ...
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