Work

Functional Inequalities for Convolution Probability Measures

Year: 2013
Type: preprint
Abstract: Let $μ$ and $ν$ be two probability measures on $\R^d$, where $μ(\d x)= \e^{-V(x)}\d x$ for some $V\in C^1(\R^d)$. Explicit sufficient conditions on $V$ and $ν$ are presented such that $μ*ν$ satisfies the log-Sobolev, Poincaré and super Poincaré inequalities. In particular, the recent results on the log-Sobolev inequality derived in \cite{Z} for convolutions of the Gaussian measure and compactly supported probability measures are improved and extended.
Language: English
Open Access status: green
OpenAlex ID: W2148408096
Cites: 19
Cited by: 6
Related to: 10