Browsing by Author "WILSON, SIMON PAUL"
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Bayesian inference for double Pareto lognormal queues
WILSON, SIMON PAUL (2010)In this article we describe a method for carrying out Bayesian inference for the double Pareto lognormal (dPlN) distribution which has recently been proposed as a model for heavy-tailed phenomena. We apply our approach ... -
Bayesian kernel projections for classification of high dimensional data
WILSON, SIMON PAUL (2011)A Bayesian multi-category kernel classification method is proposed. The algorithm performs the classification of the projections of the data to the principal axes of the feature space. The advantage of this approach is ... -
A Bayesian method for automatic landmark detection in segmented images
WILSON, SIMON PAUL (2005)The identification of landmark points of a figure in an image plays an important role in many statistical shape analysis techniques. In certain contexts, manual landmark detection is an impractical task and an ... -
Bayesian spatiotemporal model of fMRI data using transfer functions
WILSON, SIMON PAUL (2010)This research describes a new Bayesian spatiotemporal model to analyse BOLD fMRI studies. In the temporal dimension, we describe the shape of the hemodynamic response function (HRF) with a transfer function model. In ... -
Decision-theoretic approaches to display strategies in content based image retrieval
WILSON, SIMON PAUL (2004)In this report we continue development of a Bayesian CBIR system by considering the issue of an image display strategy. This is a decision problem and so within the Bayesian paradigm is to be solved by decision theory. ... -
Dependent Gaussian mixture models for source separation
WILSON, SIMON PAUL (2012)Source separation is a common task in signal processing and is often analogous to factor analysis. In this study, we look at a factor analysis model for source separation of multi-spectral image data where prior information ... -
Double Markov random fields and Bayesian image segmentation
WILSON, SIMON PAUL (IEEE, 2002)Markov random fields are used extensively in modelbased approaches to image segmentation and, under the Bayesian paradigm, are implemented through Markov chain Monte Carlo (MCMC) methods. In this paper,we describe a ... -
Estimation of asymmetry in physics
WILSON, SIMON PAUL (IEEE, 1996)The notion of asymmetry arises in many physical experiments, being a natural expression of the relative difference between two quantities. In this paper, we discuss the estimation of asymmetries between the rates of two ... -
A fast Bayesian model for a latent radio signal
FORDE, TIMOTHY KIRBY; HOULDING, BRETT; WILSON, SIMON PAUL (2009)Abstract?This paper considers the use of a recently developed Bayesian statistical approximation technique that leads to very fast determination of highly accurate estimates for latent radio signal power. Following ... -
FPGA implementation of an Image Segmentation algorithm using logarithmic arithmetic
GREGG, DAVID; WILSON, SIMON PAUL (IEEE, 2005)Image Segmentation is a process used in Computer Vision to automatically divide up an image. We investigate the suitability of FPGAs and Log Arithmetic for Image Processing. We implemented a Bayesian pixel-based ... -
Fully Bayesian source separation with application to the cosmic microwave background
WILSON, SIMON PAUL (IEEE, 2008)We address the problem of source separation in the presence of prior information. We develop a fully Bayesian source separation technique that assumes a very flexible model for the sources, namely the Gaussian mixture ... -
Image segmentation using the double Markov random field, with application to land use estimation
WILSON, SIMON PAUL (IEEE, 2001)We describe the double Markov random field, a natural hierarchical model for a Bayesian approach to model-based textured image segmentation. The model is difficult to implement, even using Markov chain Monte Carlo (MCMC) ... -
Improving CBIR by modelling the search process: a Bayesian approach
WILSON, SIMON PAUL (2006)In this paper we look at a simple image retrieval with relevance feedback scenario where we model simple properties of the search process. A content-based image retrieval method based on Bayesian inference is proposed ... -
Nonparametric analysis of the order-statistic model in software reliability
WILSON, SIMON PAUL (IEEE, 2007)In the literature on statistical inference in software reliability, the assumptions of parametric models and random sampling of bugs have been pervasive. We argue that both assumptions are problematic, the first because ... -
Parameter estimation for a model with both imperfect test and repair
WILSON, SIMON PAUL (IEEE, 2007)We describe estimation of the parameters of a manufacturing test and repair model using data available from that test. The model allows imperfect testing and imperfect repair. The principal problem that we address is ... -
Reliability assessment from fatigue micro-crack data
TAYLOR, DAVID; WILSON, SIMON PAUL (IEEE, 1997)Summary & Conclusions -Micro-cracks are generally defined to be cracks less than 1 nun in length, which propagate under cyclic stresses until they grow large and cause failure in an item (eg, component or structure). This ... -
Robust Scale Estimation for the Generalized Gaussian Probability Density Function
DAHYOT, ROZENN; WILSON, SIMON PAUL (2006) -
A split Poisson process model for the occurrence of defects and change requests during user acceptance testing
WILSON, SIMON PAUL (Trinity College Dublin, 2005)Software developed for a specific customer under contract typically undergoes a period of testing by the customer before acceptance. This is known as user acceptance testing and the process can reveal both defects in ... -
The use of Bayesian statistics to predict patterns of spatial repeatability
WILSON, SIMON PAUL (Elsevier, 2006)Statistical spatial repeatability (SSR) is an extension to the well known concept of spatial repeatability. SSR states that the mean of many patterns of dynamic tyre force applied to a pavement surface is similar for a ...