Spline-Interpolation-Based FFT Approach to Fast Simulation of Multivariate Stochastic Processes

<table>Flow scheme of building spline interpolation function <svg height="20.975" id="M37" style="vertical-align:-4.77652pt" version="1.1" viewbox="0 0 48.875 20.975" width="48.875" xmlns="http://www.w3.org/2000/svg">
<g transform="matrix(1.25,0,0,-1.25,0,20.975)">
<g transform="translate(72,-55.22)">
<text transform="matrix(1,0,0,-1,-69.43,62.57)">
<tspan style="font-size: 12.50px; " x="0" y="0"></tspan>
<tspan style="font-size: 12.50px; " x="-2.52" y="2.54">𝐻</tspan>
</text>
<text transform="matrix(1,0,0,-1,-59.91,56.91)">
<tspan style="font-size: 8.75px; " x="0" y="0">𝑗</tspan>
<tspan style="font-size: 8.75px; " x="3.4045279" y="0">𝑚</tspan>
</text>
<text transform="matrix(1,0,0,-1,-49.79,60.03)">
<tspan style="font-size: 12.50px; " x="0" y="0">(</tspan>
<tspan style="font-size: 12.50px; " x="4.1634989" y="0">𝜔</tspan>
<tspan style="font-size: 12.50px; " x="12.678042" y="0">)</tspan>
</text>
</g>
</g>
</svg>.</table>

Mathematical Problems in Engineering

fig1

Figure 1

Figure 1: Spline-Interpolation-Based FFT Approach to Fast Simulation of Multivariate Stochastic Processes 