On the high-SNR conditional maximum-likelihood estimator full statistical characterization

Abstract : In the field of asymptotic performance characterization of the conditional maximum-likelihood (CML) estimator, asymptotic generally refers to either the number of samples or the signal-to-noise ratio (SNR) value. The first case has been already fully characterized, although the second case has been only partially investigated. Therefore, this correspondence aims to provide a sound proof of a result, i.e., asymptotic (in SNR) Gaussianity and efficiency of the CML estimator in the multiple parameters case, generally regarded as trivial but not so far demonstrated.
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IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2006, 54 (12), pp.4840-4843
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Alexandre Renaux, Philippe Forster, Eric Chaumette, Pascal Larzabal. On the high-SNR conditional maximum-likelihood estimator full statistical characterization. IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, 2006, 54 (12), pp.4840-4843. 〈inria-00444708〉

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