Title :
Error Exponents for Neyman-Pearson Detection of Markov Chains in Noise
Author :
Leong, Alex S. ; Dey, Subhrakanti ; Evans, Jamie S.
Author_Institution :
Melbourne Univ., Melbourne
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 behaviour of the error exponent as the transition parameters of the Markov chain and the signal-to-noise ratio are varied. Comparisons between the high SNR asymptotics for the time-invariant and fading situations will also be made.
Keywords :
Markov processes; error analysis; fading channels; numerical analysis; Markov chains; Neyman-Pearson detection; error exponents computing; fading channels; numerical method; signal-to-noise ratio; time invariant channels; Computer networks; Detectors; Error correction; Fading; Hidden Markov models; Probability; Radar detection; Signal processing; Signal to noise ratio; Testing;
Conference_Titel :
Information, Decision and Control, 2007. IDC '07
Conference_Location :
Adelaide, Qld.
Print_ISBN :
1-4244-0902-0
Electronic_ISBN :
1-4244-0902-0
DOI :
10.1109/IDC.2007.374532
