Error Exponents for Neyman–Pearson Detection of Markov Chains in Noise

Authors:
A.S. Leong;S. Dey;J.S. Evans
Affiliations:
Melbourne Univ., Parkville;-;-
Venue:
IEEE Transactions on Signal Processing
Year:
2007

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Abstract

A numerical method for computing the error exponent for Neyman-Pearson detection of two-state Markov chains in noise is presented, for both time-invariant and fading channels. We give numerical studies showing the behavior of the error exponent as the transition parameters of the Markov chain and the signal-to-noise ratio (SNR) are varied. Comparisons between the high-SNR asymptotics in Gaussian noise for the time-invariant and fading situations will also be made.