DocumentCode
1128115
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., Parkville
Volume
55
Issue
10
fYear
2007
Firstpage
5097
Lastpage
5103
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.
Keywords
Gaussian noise; Markov processes; exponential distribution; fading channels; signal detection; Gaussian noise; Markov chains; Neyman-Pearson detection; error exponents; fading channels; time-invariant channels; Closed-form solution; Detectors; Fading; Gaussian noise; Hidden Markov models; Probability; Radar detection; Signal detection; Signal processing; Signal to noise ratio; Error exponent; Neyman–Pearson detection; fading channel; hidden Markov model (HMM);
fLanguage
English
Journal_Title
Signal Processing, IEEE Transactions on
Publisher
ieee
ISSN
1053-587X
Type
jour
DOI
10.1109/TSP.2007.897863
Filename
4305448
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