Gaussian Process property

gunbl4d3

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Dec 21, 2013
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I've found in a book the following property about gaussian processes (with zero mean) that is not proven and I am having difficulties with the proof.


Let \(\displaystyle z\) be a Gaussian process with zero mean. Then \(\displaystyle <e^z>=e^{<z^2>/2}\)


So far my approach has been


\(\displaystyle <e^z>=\int_{-\infty}^{\infty}e^zf_G(z)dz=\sum_{i=0}^{\infty} \frac{1}{i!}\int_{\infty}^{\infty}z^if_G(z)dz=\sum_{i=0}^{\infty}\frac{1}{i!}<z^i>\)


and since \(\displaystyle z\) is a gaussian process with 0 mean the odd moments vanish and we have


\(\displaystyle <e^z>=1+\frac{<z^2>}{2!}+\frac{<z^4>}{4!}+...=\sum_{n=0}^{\infty}\frac{<z^{2n}>}{(2n)!}\)


Any idea on how to continue from here?
 
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