= Deconvolution
{title2=$g=h*f\ \longmapsto\ f$}
<Deconvolution> is the <inverse problem> of recovering an input $f$ from a known response kernel $h$ and measured output $g=h*f$. The <convolution theorem> turns it into $G=HF$, but division by a small $H$ amplifies <noise> and a zero of $H$ loses information in the corresponding mode. A unique stable inverse requires assumptions on the operator and admissible inputs; a formal <Fourier transform> quotient alone does not establish either property.
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