Convergence rate of wavelet expansions of Gaussian random processes

TL;DR

This paper analyzes how quickly wavelet expansions of stationary Gaussian processes converge uniformly in probability, providing insights into their convergence rates.

Contribution

It characterizes the uniform convergence rate of wavelet expansions for stationary Gaussian processes, a novel theoretical result.

Findings

Established convergence rate bounds in probability

Applicable to broad classes of Gaussian processes

Enhances understanding of wavelet approximation accuracy

Abstract

The paper characterizes uniform convergence rate for general classes of wavelet expansions of stationary Gaussian random processes. The convergence in probability is considered.