This is a continuation of the first author’s earlier paper [17] jointly with Pang and Deng, in which the authors established some sufficient conditions under which the Euler–Maruyama (EM) method can reproduce the almost sure exponential stability of the test hybrid SDEs. The key condition imposed in [17] is the global Lipschitz condition. However, we will show in this paper that without this gl...

Computerized tomography (CT) plays an important role in medical imaging, especially for diagnosis and therapy. However, higher radiation dose from CT will result in increasing of radiation exposure in the population. Therefore, the reduction of radiation from CT is an essential issue. Expectation maximization (EM) is an iterative method used for CT image reconstruction that maximizes the likeli...

A novel method of quantifying the level of detail preservation ability of digital filters is proposed. The method assumes only the input distribution of the filter and estimates how much the filter changes the signal. The change is measured by the expectation of the absolute difference between the input and output signal. The method is applicable for many filters and input distributions. As an ...

This paper examines the Dirichlet model describing consumer behaviour. The model estimates brand performance measures in the case of repeat purchases over a set of brands. The Dirichlet model relies on some assumptions such as stationarity and the fact that the market is unsegmented. Its formulation derives from a combination of the Negative Binomial and the Dirichlet distributions. Various est...

We propose a rigorous study of an ierative maximization algo rithm introduced by Geyer and Thompson for maximum likelihood estimation of Markov random elds One step of the algorithm consists in a Monte Carlo approximation of the likelihood followed by a local maximization in the neigh borhood of the current parameter We study convergence properties of the induced process and bound the computati...

This paper proposes a Markov random field (MRF) model-based method for unsupervised segmentation of multispectral images consisting of multiple textures. To model such textured images, a hierarchical MRF is used with two layers, the first layer representing an unobservable region image and the second layer representing multiple textures which cover each region. This method uses the Expectation ...

The parameters of reconstruction iteration and subset of the ordered subset expectation maximization (OS-EM) method have a great impact on image quality. In a cerebral blood flow (CBF) examination, it is critical to produce consistent results when analyzing clinical data. We evaluated the number of iterations and subset of the OS-EM method to stabilize image quality using a normal case and an i...