On small deviations of stationary Gaussian processes and related analytic inequalities

TL;DR

This paper derives bounds on small deviations of stationary Gaussian processes using spectral analysis, Toeplitz forms, and decoupling inequalities, providing new inequalities and comparisons for continuous and discrete cases.

Contribution

It introduces novel bounds for small deviations of stationary Gaussian processes, connecting spectral properties with probabilistic inequalities, and compares different analytical approaches.

Findings

Established bounds for discrete stationary Gaussian sequences.

Derived exponential bounds for continuous Gaussian processes.

Compared Toeplitz form methods with decoupling inequalities.

Abstract

Let $ \{X_j, j\in \Z\}$ be a Gaussian stationary sequence having a spectral function $F$ of infinite type. Then for all $n$ and $z\ge 0$,$$ \P\Big\{\sup_{j=1}^n |X_j|\le z \Big\}\le \Big(\int_{-z/\sqrt{G(f)}}^{z/\sqrt{G(f)}} e^{-x^2/2}\frac{\dd x}{\sqrt{2\pi}} \Big)^n,$$ where $ G(f)$ is the geometric mean of the Radon Nycodim derivative of the absolutely continuous part $f$ of $F$. The proof uses properties of finite Toeplitz forms. Let $ \{X(t), t\in \R\}$ be a sample continuous stationary Gaussian process with covariance function $\g(u) $. We also show that there exists an absolute constant $K$ such that for all $T>0$, $a>0$ with $T\ge \e(a)$, $$\P\Big\{\sup_{0\le s,t\le T} |X(s)-X(t)|\le a\Big\} \le \exp \Big \{-{KT \over \e(a) p(\e(a))}\Big\} ,$$ where $\e (a)= \min\big\{b>0: \d (b)\ge a\big\}$, $\d (b)=\min_{u\ge 1}\{\sqrt{2(1-\g((ub))}, u\ge 1\}$, and $ p(b) = 1+\sum_{j=2}^\infty {|2\g (jb)-\g ((j-1)b)-\g ((j+1)b)| \over 2(1-\g(b))}$. The proof is based on some decoupling inequalities arising from Brascamp-Lieb inequality. Both approaches are developed and compared on examples. Several other related results are established.