We consider sparse signals embedded in
additive white noise. We study parametrically optimal as well as tree-search
sub-optimal signal detection policies. As a special case, we consider a constant
signal and Gaussian noise, with and without data outliers present. In the
presence of outliers, we study outlier resistant robust detection techniques.
We compare the studied policies in terms of error performance, complexity and
resistance to outliers.
Cite this paper
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