Neyman-pearson detection of gauss-Markov signals in noise: closed-form error exponentand properties

DOI10.1109/TIT.2006.871599zbMath1298.94029arXivcs/0506028MaRDI QIDQ3547679

H. Vincent Poor, Lang Tong, Youngchul Sung

Publication date: 21 December 2008

Published in: IEEE Transactions on Information Theory (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/cs/0506028

zbMATH Keywords

Autoregressive processerror exponentGauss-Markov modelcorrelated signalNeyman-Pearson detection

Mathematics Subject Classification ID

Gaussian processes (60G15) Signal detection and filtering (aspects of stochastic processes) (60G35) Signal theory (characterization, reconstruction, filtering, etc.) (94A12) Detection theory in information and communication theory (94A13) Markov renewal processes, semi-Markov processes (60K15)

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