In this paper, a three dimensional geometrical scattering channel model for indoor and outdoor wireless propagation environments is introduced. It is based on the assumption that the scatterers are distributed within a spheroid, in which the mobile station and base station are located at the spheroid’s foci. This model captures both the spatial and temporal statistical distributions of the rece...

Assume that n points P1, . . . , Pn are distributed independently and uniformly in the triangle with vertices (0, 1), (0, 0), and (1, 0). Consider the convex hull of (0, 1), P1, . . . , Pn, and (1, 0). The vertices of the convex hull form a convex chain. Let p (n) k be the probability that the convex chain consists — apart from the points (0, 1) and (1, 0) — of exactly k of the points P1, . . ....

We address the problem of recognizing the pose of an object category from video sequences capturing the object under small camera movements. This scenario is relevant in applications such as robotic object manipulation or autonomous navigation. We introduce a new algorithm where wemodel an object category as a collection of non parametric probability densities capturing appearance and geometric...

Clustering is an important task in the Data Mining. Clustering on uncertain data is a challenging in both modeling similarity between objects of uncertain data and developing efficient computational method. The most of the previous method extends partitioning clustering methods and Density based clustering methods, which are based on geometrical distance between two objects. Such method cannot ...

The distribution of spatial domain structures originated during one- and three-dimensional Poisson-Voronoi transformations are computed analytically extending the recently obtained results for the two-dimensional case. The presented method gives a full description of the developed microstructure and is valid for tessellations of any dimensionality. The temporal and spatial dependences of the do...

We investigate a model of an evolving random network, introduced by us previously [Phys. Rev. Lett. 83, 5587 (1999)]. The model is a generalization of the Bak-Sneppen model of biological evolution, with the modification that the underlying network can evolve by adding and removing sites. The behavior and the averaged properties of the network depend on the parameter p, the probability to establ...

He obtained his Ph.D. from Stanford University in 1982 and since then has done research in various areas including geometrical probability, multivariate probability inequalities and survival analysis. This work is part of an ongoing project devoted to the modeling the relationship between species distribution and climate variables. Boulder for providing us with species and climate data. Abstrac...