When does a Gaussian process have an infinitely divisible square?
Haya Kaspi (Technion and Boston University) We shall show that up to a multiplication by a constant function, a Gaussian process has an infinitely divisible square if and only if, its covariance is the potential density of a transient symmetric Markov process. The lecture is based on the paper: “A characterization of the infinitely divisible squared Gaussian processes”, By Nathalie Eisenbaum and Haya Kaspi. You may download a preprint from Haya Kaspi’s homepage at http://ie.technion.ac.il/iehaya/phtml Tuesday, December 14, 2004 Self-similarity in natural images: the smoothness issue Francois Roueff (Ecole Normale Superieure des Telecommunications, Paris) Our primary goal here is to model smoothness in images. Two basic properties for modeling images are often considered: self-similarity and stationarity. A third property, the occlusion phenomenon, should also be taken into account as it is specific to the formation process of images. Although these properties are idealizations of the r
