We consider the class of real-valued stochastic processes indexed
on a compact subset of R or R2 with
almost surely absolutely continuous sample paths. We obtain an
implicit formula for the distributions of their maxima. The main
result is the derivation of numerical bounds that turn out to be
very accurate, in the Gaussian case, for levels that are not
large. We also present the first explicit upper bound for the
distribution tail of the maximum in the two-dimensional Gaussian
framework. Numerical comparisons are performed with known tools
such as the Rice upper bound and expansions based on the Euler
characteristic. We deal numerically with the determination of the
persistence exponent.
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