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—Recently, a new adaptive scheme [Conte et al.] has been introduced for covariance structure matrix estimation in the context of adaptive radar detection under non-Gaussian noise. This latter has been modeled by compound-Gaussian noise, which is the product c of the square root of a positive unknown variable (deterministic or random) and an independent(More)
—Minimal bounds on the mean square error (MSE) are generally used in order to predict the best achievable performance of an estimator for a given observation model. In this paper, we are interested in the Bayesian bound of the Weiss–Weinstein family. Among this family, we have Bayesian Cramér-Rao bound, the Bo-brovsky–MayerWolf–Zakaï bound, the Bayesian(More)
In the field of asymptotic performance characterization of 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(More)
[1] The radiative effects from increased concentrations of well-mixed greenhouse gases (WMGHGs) represent the most significant and best understood anthropogenic forcing of the climate system. The most comprehensive tools for simulating past and future climates influenced by WMGHGs are fully coupled atmosphere-ocean general circulation models (AOGCMs).(More)
This correspondence deals with the problem of estimating signal parameters using an array of sensors. In source localization, two main Maximum Likelihood methods have been introduced: the Conditional Maximum Likelihood method which assumes the source signals nonrandom and the Unconditional Maximum Likelihood method which assumes the source signals random.(More)