We prove a new variant of comparison principle for logarithmic $L_2$-small ball probabilities of Gaussian processes. As an application, we obtain logarithmic small ball asymptotics for some well-known processes with smooth covariances.
Comparison theorems for the small ball probabilities of Gaussian processes in weighted $L_2$-norms
Integration-by-Parts Characterizations of Gaussian Processes
Expansions for Gaussian processes and Parseval frames
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