... problem of detecting a target inGaussiannoisewithunknown covariance ...matrix. In contrast to the usual assumption of deterministic target ampli- tudes, we ...
... the detectionof an unknown and arbitrary rank-one signal in a spatial sector scanned by a small number of ...problem of finding the maximal invariant for the ...
... Department of Electronics, Optronics and Signal 10 Avenue Edouard Belin, 31055 Toulouse France Abstract—Adaptive detectionof a Swerling I-II type target inGaussiannoise ...
... account for e.g. weak-amplitude signals, T wave overlaps and non-Gaussiannoise ...distribution. In this paper, we develop several detectors using the generalized ...
... problem of detecting a signal of interest in the presence ofGaussiannoisewith un- known statistics when the number of training samples available to learn ...
... Adaptive detectionof distributed targets has been addressed in [1] and [2]; noise is modeled in terms of independent, com- plex normal random vectors with a common ...
... out of the zero-voltage state provides a sensitive threshold detector because the switching rate varies exponentially with the bias ...periment in which a current-biased Josephson junction is ...
... hat in der Literatur grosse Beachtung ...CUSUM-Algorithmus. In vielen Anwendungsgebieten, wie ...sind in den meisten praktischen Anwendungen unbekannt und mu¨ssen gescha¨tzt ...Maximum ...
... esis test based on the likelihood functions for double-talk versus a channel ...hypothesis test differs from the one pro- posed in [8], which involved the channel input ( ...
... function of ξ rather than just a trigonometric polynomial in ξ. In other words, we deal here with the class of sequences in ` 1 whose Fourier transform is a trigonometric ...
... The restriction on the location of the zeros of E(s)/F(s) will not be met in practical cases. The penalty for attempting this operation is that the noise power d[r] ...
... need for our study. Then, section III, the core of the paper, is devoted to the maximum likelihood estimation (MLE) of a parameter θ, observed via n samples through a possibly nonlinear ...
... contrast with the simplicity of this model and even when the noise background is white and Gaussian, the decision can be ...Actually, in many applications, very little is known about ...
... problem of estimating the parameters of multivariate generalizedGaussian distributions using the maximum likelihood ...method. For any shape param- eter , we have proved that ...
... number of low intensity components are lost when using a data fidelity term derived from Poisson ...shape of low intensity components is not well reconstructed when using a WL2 data fidelity ...obtained ...
... robustness of deconvolution estimators as pointed out in [Meister, 2004] where the author established that the mean integrated squared error of such an estimator can grow to infinity when the ...
... example of fading distribution for which the above conditions can be ...10 with probability half and let v = 1/4. Let µ = 5/4, then for any values of P , the maximizer of (24) is ...
... distribution with . This seems to indicate that ACE is (close to) optimum for a large class of nonhomogeneous environments, at least it is rather ro- bust to covariance mismatches characterized by ...
... To show that we can indeed use the opposite parallactic angles technique to estimate the residual noise level, we compare the empirical complementary CDF of the detection map in three di[r] ...
... ] in the late twenties, play an important role in applied ...] in 1967, the large dimensional setting (where the dimension of the observations is of the same order as the size of ...