Worst case additive noise for binary-input channels and zero-threshold detection under constraints of power and divergence

A.L. McKellips, S. Verdu
1997 IEEE Transactions on Information Theory  
Additive-noise channels with binary inputs and zerothreshold detection are considered. We study worst case noise under the criterion of maximum error probability with constraints on both power and divergence with respect to a given symmetric nominal noise distribution. Particular attention is focused on the cases of a) Gaussian nominal distributions and b) asymptotic increase in worst case error probability when the divergence tolerance tends to zero. Index Terms-Detection, Gaussian error
more » ... ility, hypothesis testing, Kullback-Leibler divergence, least favorable noise.
doi:10.1109/18.605590 fatcat:4676zz4movfbrmnit3epkw5oty