We develop the extended dynamical mean field theory (E-DMFT) with a view towards realistic applications. 1) We introduce an intuitive derivation of the E-DMFT formalism. By identifying the Hartree contributions before the EDMFT treatment, it allows to handle systems in symmetry breaking phases within a simple formalism. 2) We make a new implementation of E-DMFT through real Hubbard-Stratonovich...

In this paper we address the problem of building convenient criteria to solve linear and noisy inverse problems of the form y = Ax + n. Our approach is based on the speciication of constraints on the solution x through its belonging to a given convex set C. The solution is chosen as the mean of the distribution which is the closest to a reference measure on C with respect to the Kullback diverg...

BACKGROUND Colour image segmentation is fundamental and critical for quantitative histological image analysis. The complexity of the microstructure and the approach to make histological images results in variable staining and illumination variations. And ultra-high resolution of histological images makes it is hard for image segmentation methods to achieve high-quality segmentation results and ...

This paper is concerned with the numerical approximation of mean curvature flow t → Ω(t) satisfying an additional inclusion-exclusion constraint Ω1 ⊂ Ω(t) ⊂ Ω2. Classical phase field model to approximate these evolving interfaces consists in solving the AllenCahn equation with Dirichlet boundary conditions. In this work, we introduce a new phase field model, which can be viewed as an Allen Cahn...

It was found that the traditional Mean Shift algorithm segmentation often produces the connection channel, several categories between clusters can not be completely separated from the problem, an improved classification of the structured mean shift segmentation algorithm iterations to obtain the initial cluster in center on the basis of different bandwidth matrix stepwise clustering, resulting ...

In this paper we address the problem of building convenient criteria to solve linear and noisy inverse problems of the form y = Ax + n. Our approach is based on the speci cation of constraints on the solution x through its belonging to a given convex set C. The solution is chosen as the mean of the distribution which is the closest to a reference measure on C with respect to the Kullback diverg...

This paper describes a method for recognizing partially occluded and/or destroyed objects using an eigenspace method referred to as a ‘mean eigenwindow’ method that stores multiple partially occluded/destroyed objects in an eigenspace. We have proposed to store similar poses, that may include disturbed shapes, of an object in a particular window referred to as the ‘eigen window’ and, finally, m...

This paper deals with two subjects. First, we will show how support vector machine (SVM) regression problem can be solved as the maximum a posteriori prediction in the Bayesian framework. The second part describes an approximation technique that is useful in performing calculations for SVMs based on the mean ÿeld algorithm which was originally proposed in Statistical Physics of disordered syste...

Recently much attention has been paid to the nonextensive canonical distributions: the αfamilies. Such distributions have been found in many real-world systems such as fully developed turbulence and financial markets. In this paper, a generalized mean-field method to approximate the expectations of the α-families is proposed. We calculate the α′-projection of a probability distribution to find ...