Gaussian process and white noise model
A maxiset approach of a Gaussian white noise model
... L’archive ouverte pluridisciplinaire HAL, est destin´ee au d´epˆot et `a la diffusion de documents scientifiques de niveau recherche, publi´es ou non, ´emanant des ´etablissements d’ense[r] ...
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Some Applications of Higher Moments of the Linear Gaussian White Noise Process
... − α quartile of the χ 2 ( ) m distribution. 3.3. Determining the Optimal Value of d Figure 1 suggests two growth models: 1) the quadratic growth model and 2) ex- ponential growth model. We are going to use ...
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TAR modeling with missing data when the white noise process is not Gaussian
... a process (the threshold process) {Z t } determine not only the values of the process of interest {X t }, but also its ...threshold process is the same process of interest but is ...
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Gaussian Process Training with Input Noise
... GP model had a log probability per data point of ...our model has near-symmetric ‘horns’ in the variance around the corners of the square wave, whereas MLHGP only has one ...our model, the amount of ...
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Robust Parametric Modeling of Speech in Additive White Gaussian Noise
... the noise, which is assumed to be white Gaussian, is evaluated from the least squares analysis of an overdetermined set of p lower-order Yule- Walker ...the noise variance estimator. The ...
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Characteristic Analysis of White Gaussian Noise in S Transformation Domain
... ABSTRACT The characteristic property of white Gaussian noise (WGN) is derived in S-transformation domain. The results show that the distribution of normalized S-spectrum of WGN follows χ 2 ...
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Adaptive Bernstein-von Mises theorems in Gaussian white noise
... the prior can lead to suboptimal performance (see, e.g., [ 27 ]). It therefore makes sense to use an automatic procedure, unless a practitioner is particularly confident that their prior correctly captures the fine ...
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Mind the nuisance: Gaussian process classification using privileged noise
... of Gaussian process classifiers ...the model in form of a latent variable, which modulates the noise term of the ...the noise is integrated out before obtaining the final model, ...
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The Estimation of Radial Exponential Random Vectors in Additive White Gaussian Noise
... by noise during their transmission, such as in mobile or network commu- ...proposed model for original data ...proper model for distribution of wavelet coefficients is important in wavelet-based ...
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Noise Standard Deviation Estimation for Additive White Gaussian Noise Corrupted Images using SVD Domain
... the noise standard deviation. Noise occurs when scanning the drawn image for making the cartoon ...the noise to the extent of the problem and it helps cartoon related noise ...of noise ...
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Adaptive detection of a Gaussian signal in Gaussian noise
... in Gaussian noise with unknown covariance matrix is addressed in this ...conditional model is ubiquitous, we investigate here the equivalent GLR approach for an unconditional model where the ...
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State Estimation using Gaussian Process Regression for Colored Noise Systems
... a noise signal is generally understood to be some broad characteristic of its power ...of noise have signif- icantly different properties: for example, as audio signals they will sound different to human ...
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The Gaussian Process Autoregressive Regression Model (GPAR)
... Tidal height, wind speed, and air temperature data set. 6 This data set was collected at 5 minute in- tervals by four weather stations: Bramblemet, Camber- met, Chimet, and Sotonmet, all located in Southamp- ton, UK. The ...
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Gaussian Process Model Based Predictive Control
... INTRODUCTION Model Predictive Control (MPC) is a common name for computer control algorithms that use an explicit process model to predict the future plant ...Linear model based predictive ...
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Model selection with application to gamma process and inverse Gaussian process
... gamma process and the inverse Gaussian process are suitable for modeling gradual damage in- troduced by continuous ...“wrong” model is probably larger than that of the “right” ...wrong ...
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Model selection with application to gamma process and inverse Gaussian process
... gamma process and the inverse Gaussian process are widely used in condition-based main- ...gamma process can be well approximated by an inverse Gaussian process or the other way ...
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The Performance of Fast Frequency Hopping System in Additive White Gaussian Noise (AWGN)
... and process carried on like this. This process requires a bigger bandwidth to send the same data using only one carrier ...the process continues like ...this process goes on and ...
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A gaussian process latent variable model for BRDF inference
... as white balance, differ- ent color temperatures of the head-on light and the environ- ment, differences between our capturing setup and the one in MERL, but generally we are able to create more convinc- ing ...
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Over-Fitting in Model Selection with Gaussian Process Regression
... Abstract. Model selection in Gaussian Process Regression (GPR) seeks to determine the optimal values of the hyper-parameters governing the covariance function, which allows flexible customization of ...
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A gaussian process based multi-person interaction model
... In this paper, we propose a new predictive model for a recursive Bayesian filter on the basis of Gaussian Process Regression. Us- ing the proposed method, the state vector of a pedestrian is pre- ...
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