We propose a new type SDE depending on the future distributions with all initial values and establish correspondence between this equation associated singular nonlinear PDE. Well-posedness regularities are investigated.

This chapter serves as an introduction to estimation of distribution algorithms (EDAs). Estimation of distribution algorithms are a new paradigm in evolutionary computation. They combine statistical learning with population-based search in order to automatically identify and exploit certain structural properties of optimization problems. State-of-the-art EDAs consistently outperform classical g...

Currently surrogate data analysis can be used to determine if data is consistent with various linear systems, or something else (a nonlinear system). In this paper we propose an extension of these methods in an attempt to make more specific classifications within the class of nonlinear systems. In the method of surrogate data one estimates the probability distribution of values of a test statis...

A BRDF approximation is developed that is suitable for interactive color appearance design in direct lighting provided by environment maps. The BRDFs are approximated as a linear combination of cosine lobes with a fixed set of specular exponents. A nonlinear optimization routine is used to fit the cosine lobes to BRDFs appropriate for a specific color appearance design application: automotive p...

We present a local convergence analysis of generalized Newton methods for singular smooth and nonsmooth operator equations using adaptive constructs of outer inverses. We prove that for a solution x of F(x) = 0, there exists a ball S = S(x ; r), r > 0 such that for any starting point x 0 2 S the method converges to a solution x 2 S of ?F (x) = 0, where ? is a bounded linear operator that depend...

This paper introduces a new method to register images that are rotated and translated with respect to each other. The method works by transforming each image to a gradient distribution space. This space represents the likelihood of finding a particular gradient in the image and is invariant to translation. Once transformed the rotation between the images is efficiently found using correlation. ...