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Some Fine Properties of BV Functions on Wiener Spaces

Luigi Ambrosio, Michele Miranda Jr., Diego Pallara (2015)

Analysis and Geometry in Metric Spaces

In this paper we define jump set and approximate limits for BV functions on Wiener spaces and show that the weak gradient admits a decomposition similar to the finite dimensional case. We also define the SBV class of functions of special bounded variation and give a characterisation of SBV via a chain rule and a closure theorem. We also provide a characterisation of BV functions in terms of the short-time behaviour of the Ornstein-Uhlenbeck semigroup following an approach due to Ledoux.

Some fine properties of sets with finite perimeter in Wiener spaces

Michele Miranda Jr. (2014)

Banach Center Publications

In this paper we give a brief overview on the state of art of developments of Geometric Measure Theory in infinite-dimensional Banach spaces. The framework is given by an abstract Wiener space, that is a separable Banach space endowed with a centered Gaussian measure. The focus of the paper is on the theory of sets with finite perimeter and on their properties; this choice was motivated by the fact that most of the good properties of functions of bounded variation can be obtained, thanks to coarea...

Some ideas for comparison of Bellman chains

Laurent Truffet (2003)

Kybernetika

In this paper we are exploiting some similarities between Markov and Bellman processes and we introduce the main concepts of the paper: comparison of performance measures, and monotonicity of Bellman chains. These concepts are used to establish the main result of this paper dealing with comparison of Bellman chains.

Some inequalities related to the Stam inequality

Abram Kagan, Tinghui Yu (2008)

Applications of Mathematics

Zamir showed in 1998 that the Stam classical inequality for the Fisher information (about a location parameter) 1 / I ( X + Y ) 1 / I ( X ) + 1 / I ( Y ) for independent random variables X , Y is a simple corollary of basic properties of the Fisher information (monotonicity, additivity and a reparametrization formula). The idea of his proof works for a special case of a general (not necessarily location) parameter. Stam type inequalities are obtained for the Fisher information in a multivariate observation depending on a univariate location...

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