The paper dwells into the comparison of parametric and non-parametric complex-valued 2D signal analysis, focusing the attention on complex-valued sub-meter SAR image data. The work is based on the study carried out in [1][2], [3][4] and [5]. In [1][2] a parametric Gauss-Markov Random Field (GMRF) model has been proposed for texture analysis and in [3][4] a time-frequency analysis (TFA) method h...

Continuous data arise in most areas of medicine. Familiar clinical examples include blood pressure, ejection fraction, forced expiratory volume in 1 second (FEV1), serum cholesterol, and anthropometric measurements. Methods for analysing continuous data fall into two classes, distinguished by whether or not they make assumptions about the distribution of the data. Theoretical distributions are ...

In this work parametric and non-parametric statistical methods are proposed to analyze Diffusion Tensor Magnetic Resonance Imaging (DT-MRI) data. A Multivariate Normal Distribution is proposed as a parametric statistical model of diffusion tensor data when magnitude MR images contain no artifacts other than Johnson noise. We test this model using Monte Carlo (MC) simulations of DT-MRI experimen...

We extend recent methods for parametric sequence alignment to the parameter space for scoring RNA folds. This involves the construction of an RNA polytope. A vertex of this polytope corresponds to RNA secondary structures with common branching. We use this polytope and its normal fan to study the effect of varying three parameters in the free energy model that are not determined experimentally....

The abstract domain of polyhedra lies at the heart of many program analysis techniques. However, its operations can be expensive, precluding their application to polyhedra that involve many variables. This paper describes a new approach to computing polyhedral domain operations. The core of this approach is an algorithm to calculate variable elimination (projection) based on parametric linear p...

Survival analysis has been a topic of active statistical research in the past few decades with applications spread across several areas. Traditional applications usually consider data with only a small numbers of predictors with a few hundreds or thousands of observations. Recent advances in data acquisition techniques and computation power have led to considerable interest in analyzing very-hi...

The paper provides a method of topological analysis of gray scale images and other images with parameters. The main goal is to count objects in the image and extract them without image segmentation. The approach is simple and context independent. The method is based on algebraic topology, the mathematical theory responsible for these issues.

In the area of automatic parallelization of programs, analyzing and transforming loop nests with parametric aane loop bounds requires fundamental mathematical results. The most common geometrical model of iteration spaces, called the polytope model, is based on mathematics dealing with convex and discrete geometry, linear programming, combinatorics and geometry of numbers. In this paper, we pre...