Searcharxiv⌕ Search

arXiv subjects

Liming Wu

Publications and source records attributed to Liming Wu.

43 records · Page 3Linked to original sources

Uniqueness of a pre-generator for $C_0$-semigroup on a general locally convex vector space

The main purpose is to generalize a theorem of Arendt about uniqueness of $C_0$-semigroups from Banach space setting to the general locally convex vector spaces, more precisely, we show that cores are the only domains of uniqueness for $C_0$-semigroups on locally convex spaces. As an application, we find a necessary and sufficient condition for that the mass transport equation has one unique $L^1(\R^d,dx)$ weak solution.

math.FA↗

Lyapunov conditions for logarithmic Sobolev and Super Poincaré inequality

We show how to use Lyapunov functions to obtain functional inequalities which are stronger than Poincaré inequality (for instance logarithmic Sobolev or $F$-Sobolev). The case of Poincaré and weak Poincaré inequalities was studied in Bakry and al. This approach allows us to recover and extend in an unified way some known criteria in the euclidean case (Bakry-Emery, Wang, Kusuoka-Stroock ...).

math.PR↗

Transportation-information inequalities for Markov processes

In this paper, one investigates the following type of transportation-information $T_cI$ inequalities: $α(T_c(ν,μ))\le I(ν|μ)$ for all probability measures $ν$ on some metric space $(\XX, d)$, where $μ$ is a given probability measure, $T_c(ν,μ)$ is the transportation cost from $ν$ to $μ$ with respect to some cost function $c(x,y)$ on $\XX^2$, $I(ν|μ)$ is the Fisher-Donsker-Varadhan information of $ν$ with respect to $μ$ and $α: [0,\infty)\to [0,\infty]$ is some left continuous increasing function. Using large deviation techniques, it is shown that $T_cI$ is equivalent to some concentration inequality for the occupation measure of a $μ$-reversible ergodic Markov process related to $I(\cdot|μ)$, a counterpart of the characterizations of transportation-entropy inequalities, recently obtained by Gozlan and Léonard in the i.i.d. case . Tensorization properties of $T_cI$ are also derived.

math.PR↗

Moderate deviations for non-linear functionals and empirical spectral density of moving average processes

A moderate deviation principle for functionals, with at most quadratic growth, of moving average processes is established. The main assumptions on the moving average process are a Logarithmic Sobolev inequality for the driving random variables and the continuity, or weaker, of the spectral density of the moving average process. We also obtain the moderate deviations for the empirical spectral density, exhibiting an interesting new form of the rate function, i.e. with a correction term compared to the Gaussian rate functionnal.

math.PR↗