107,505 research outputs found
LUC BESSON . EL FUTURO ES MODEMO
No full textJavier G. Romero (2001). LUC BESSON . EL FUTURO ES MODEMO. Nosferatu. Revista de cine. (34). https://riunet.upv.es/handle/10251/41212.Importación Masiva3
GLRT-Based Direction Detectors in Homogeneous Noise and Subspace Interference
No full textIn this paper, we derive and assess decision schemes to discriminate, resorting to an array of sensors, between the H0 hypothesis that data under test contain disturbance only (i.e., noise plus interference) and the H1 hypothesis that they also contain signal components along a direction which is a priori unknown but constrained to belong to a given subspace of the observables. The disturbance is modeled in terms of complex normal random vectors plus deterministic interference assumed to belong to a known subspace. We assume that a set of noise-only (secondary) data is available, which possess the same statistical characterization of noise in the cells under test. At the design stage, we resort to either the plain generalized-likelihood ratio test (GLRT) or the two-step GLRT-based design procedure. The performance analysis, conducted resorting to simulated data, shows that the one-step GLRT performs better than the detector relying on the two-step design procedure when the number of secondary data is comparable to the number of sensors; moreover, it outperforms a one-step GLRT-based subspace detector when the dimension of the signal subspace is sufficiently high
Compte rendu du Ve colloque de linguistique latine. Actes du Ve Colloque de linguistique latine/Proceedings of the V° Colloquium on Latin Linguistics, Louvain-La-Neuve/ Borzee, 31 mars - 4 avril 1989, édités par M. Lavency et D. Longrée, Cahiers de l'Institut de Linguistique de Louvain, 15. 1-4, Louvain-La-Neuve, 1989
No full textBesson G. Compte rendu du Ve colloque de linguistique latine. Actes du Ve Colloque de linguistique latine/Proceedings of the V° Colloquium on Latin Linguistics, Louvain-La-Neuve/ Borzee, 31 mars - 4 avril 1989, édités par M. Lavency et D. Longrée, Cahiers de l'Institut de Linguistique de Louvain, 15. 1-4, Louvain-La-Neuve, 1989. In: L'Information Grammaticale, N. 47, 1990. pp. 51-52
Compte rendu du Ve colloque de linguistique latine. Actes du Ve Colloque de linguistique latine/Proceedings of the V° Colloquium on Latin Linguistics, Louvain-La-Neuve/ Borzee, 31 mars - 4 avril 1989, édités par M. Lavency et D. Longrée, Cahiers de l'Institut de Linguistique de Louvain, 15. 1-4, Louvain-La-Neuve, 1989
No full textBesson G. Compte rendu du Ve colloque de linguistique latine. Actes du Ve Colloque de linguistique latine/Proceedings of the V° Colloquium on Latin Linguistics, Louvain-La-Neuve/ Borzee, 31 mars - 4 avril 1989, édités par M. Lavency et D. Longrée, Cahiers de l'Institut de Linguistique de Louvain, 15. 1-4, Louvain-La-Neuve, 1989. In: L'Information Grammaticale, N. 47, 1990. pp. 51-52
CFAR matched direction detector
No full textIn a previously published paper by Besson et al., we considered the problem of detecting a signal whose associated spatial signature is known to lie in a given linear subspace, in the presence of subspace interference and broadband noise of known level. We extend these results to the case of unknown noise level. More precisely, we derive the generalized-likelihood ratio test (GLRT) for this problem, which provides a constant false-alarm rate (CFAR) detector. It is shown that the GLRT involves the largest eigenvalue and the trace of complex Wishart matrices. The distribution of the GLRT is derived under the hypothesis. Numerical simulations illustrate its performance and provide a comparison with the GLRT when the noise level is known
An ABORT-like detector with improved mismatched signals rejection capabilities
No full textIn this paper, we present a GLRT-based adaptive detection algorithm for extended targets with improved rejection capabilities of mismatched signals. We assume that a set of secondary data is available and that noise returns in primary and secondary data share the same statistical characterization. To increase the selectivity of the detector, similarly to the ABORT formulation, we modify the hypothesis testing problem at hand introducing fictitious signals under the null hypothesis. Such unwanted signals are supposed to be orthogonal to the nominal steering vector in the whitened observation space. The performance assessment, carried out by Monte Carlo simulation, shows that the proposed dectector ensures better rejection capabilities of mismatched signals than existing ones, at the price of a certain loss in terms of detection of matched signals
Direction detector for distributed targets in unknown noise and interference
No full textAdaptive detection of distributed radar targets in homogeneous Gaussian noise plus subspace interference is addressed. It is assumed that the actual steering vectors lie along a fixed and unknown direction of a preassigned and known subspace, while interfering signals are supposed to belong to an unknown subspace, with directions possibly varying from one resolution cell to another. The resulting detection problem is formulated in the framework of statistical hypothesis testing and solved using an ad hoc algorithm strongly related to the generalised likelihood ratio test. A performance analysis, carried out also in comparison to natural benchmarks, is presented
Colloque : « Fantasy et Histoire(s) »
No full textColloque des Imaginales : « Fantasy et Histoire(s) » Epinal, Parc du Cours, dans le Magic Mirror « Salon perdu » 22-23 mai 2018 Direction scientifique : Anne Besson (Université d’Artois), Christian Chelebourg (Université de Lorraine), Stéphanie Nicot (directrice artistique des Imaginales), Natacha Vas-Deyres (Université de Bordeaux-Montaigne) Comité d’organisation : Stéphane Wieser (directeur du Festival des Imaginales d’Epinal), en association avec le Comité d’Histoire régionale – Région G..
Adaptive detection of distributed targets in compound-Gaussian noise without secondary data: A Bayesian approach
No full textIn this paper, we deal with the problem of adaptive detection of distributed targets embedded in colored noise modeled in terms of a compound-Gaussian process and without assuming that a set of secondary data is available.The covariance matrices of the data under test share a common structure while having different power levels. A Bayesian approach is proposed here, where the structure and possibly the power levels are assumed to be random, with appropriate distributions. Within this framework we propose GLRT-based and ad-hoc detectors. Some simulation studies are presented to illustrate the performances of the proposed algorithms. The analysis indicates that the Bayesian framework could be a viable means to alleviate the need for secondary data, a critical issue in heterogeneous scenarios
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