Abstract
Abstract
We consider stochastic processes
{Y(t)}
which can be represented as
{Y(t)=(X(t))^{s}}
,
{s\in\mathbb{N}}
, where
{X(t)}
is a stationary strictly sub-Gaussian process, and build a wavelet-based model that simulates
{Y(t)}
with given accuracy and reliability in
{L_{p}([0,T])}
.
A model for simulation with given accuracy and reliability in
{L_{p}([0,T])}
is also built for processes
{Z(t)}
which can be represented as
{Z(t)=X_{1}(t)X_{2}(t)}
, where
{X_{1}(t)}
and
{X_{2}(t)}
are independent stationary strictly sub-Gaussian processes.
Subject
Applied Mathematics,Statistics and Probability