Zobrazeno 1 - 10
of 211
pro vyhledávání: '"Philippe Forster"'
Publikováno v:
Circuits, Systems, and Signal Processing. 39:4740-4761
Various methods have been proposed to estimate the direction of arrival (DOA) of sources under the assumption of Gaussian noise. This assumption, based on the central limit theorem, has been mainly used because it offers an appropriate model in a hom
Publikováno v:
IEEE Signal Processing Letters. 26:367-371
The joint estimation of means and scatter matrices is often a core problem in multivariate analysis. In order to overcome robustness issues, such as outliers from Gaussian assumption, M-estimators are now preferred to the traditional sample mean and
Efficient Estimation of Kronecker Product of Linear Structured Scatter Matrices under t-distribution
Publikováno v:
28th European Signal Processing Conference (EUSIPCO 2020)
28th European Signal Processing Conference (EUSIPCO 2020), Jan 2021, Amsterdam, Netherlands. ⟨10.23919/eusipco47968.2020.9287415⟩
HAL
28th European Signal Processing Conference (EUSIPCO 2020), Jan 2021, Amsterdam, Netherlands
EUSIPCO
28th European Signal Processing Conference (EUSIPCO 2020), Jan 2021, Amsterdam, Netherlands. ⟨10.23919/eusipco47968.2020.9287415⟩
HAL
28th European Signal Processing Conference (EUSIPCO 2020), Jan 2021, Amsterdam, Netherlands
EUSIPCO
International audience; This paper addresses structured scatter matrix estimation within the non convex set of Kronecker product structure. The latter model usually involves two matrices , which can be themselves linearly constrained, and arises in m
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c94d642b9e0fc1d9cbd46706d03739cb
https://hal.science/hal-02873816
https://hal.science/hal-02873816
Publikováno v:
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TSP.2020.3042946⟩
IEEE Transactions on Signal Processing, 2021, 69, pp.603-616. ⟨10.1109/TSP.2020.3042946⟩
IEEE Transactions on Signal Processing, Institute of Electrical and Electronics Engineers, In press, ⟨10.1109/TSP.2020.3042946⟩
IEEE Transactions on Signal Processing, 2021, 69, pp.603-616. ⟨10.1109/TSP.2020.3042946⟩
International audience; The estimation of covariance matrices is a core problem in many modern adaptive signal processing applications. For matrix-and array-valued data, e.g., MIMO communication, EEG/MEG (time versus channel), the covariance matrix o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4a5420f6a56782b36818a4d111208b94
https://hal.archives-ouvertes.fr/hal-03039552
https://hal.archives-ouvertes.fr/hal-03039552
Publikováno v:
Signal Processing
Signal Processing, 2019, 165, pp.163-174. ⟨10.1016/j.sigpro.2019.06.030⟩
Signal Processing, Elsevier, 2019, 165, pp.163-174. ⟨10.1016/j.sigpro.2019.06.030⟩
Signal Processing, 2019, 165, pp.163-174. ⟨10.1016/j.sigpro.2019.06.030⟩
Signal Processing, Elsevier, 2019, 165, pp.163-174. ⟨10.1016/j.sigpro.2019.06.030⟩
International audience; Covariance matrix estimation is a ubiquitous problem in signal processing. In most modern signal processing applications, data are generally modeled by non-Gaussian distributions with covariance matrices exhibiting a particula
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ced6344432c8477a28377018518a7083
https://hal.science/hal-02165848
https://hal.science/hal-02165848
Publikováno v:
EURASIP Journal on Advances in Signal Processing, Vol 2010 (2010)
This paper deals with the imaging of a moving target using a multifrequency and multistatic radar consisting in one receiver and several narrowband transmitters. Considering two hypotheses about the studied target, we derive two multistatic inverse s
Externí odkaz:
https://doaj.org/article/45f0cb01dc424cb7a18341051c1ad3a7
Publikováno v:
IEEE Transactions on Geoscience and Remote Sensing
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2017, 55 (6), p. 3248-3260. ⟨10.1109/TGRS.2017.2666267⟩
IEEE Transactions on Geoscience and Remote Sensing, Institute of Electrical and Electronics Engineers, 2017, 55 (6), p. 3248-3260. ⟨10.1109/TGRS.2017.2666267⟩
International audience; When using multichannel synthetic aperture radar (MSAR) to perform moving target detection, the coherence between the received signals is closely linked to the detection capacities of the system. In airborne MSAR context, beca
Publikováno v:
ICASSP
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2019. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2019. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, May 2019, Brighton, United Kingdom. ⟨10.1109/ICASSP.2019.8683058⟩
ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2019. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
ICASSP 2019. IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), IEEE, May 2019, Brighton, United Kingdom. ⟨10.1109/ICASSP.2019.8683058⟩
International audience; This paper introduces an improved Low Rank Adaptive Normalized Matched Filter (LR-ANMF) detector in a high dimensional (HD) context where the observation dimension is large and of the same order of magnitude than the sample si
Publikováno v:
HAL
IEEE CAMSAP 2019
IEEE CAMSAP 2019, IEEE, Dec 2019, Gosier, France
CAMSAP
IEEE CAMSAP 2019
IEEE CAMSAP 2019, IEEE, Dec 2019, Gosier, France
CAMSAP
We consider the problem of detecting a known $M$ -dimensional target signature vector from an observation corrupted by an additive noise with unknown covariance matrix. In that case, standard statistical methods of detection usually assume that $N$ -
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8cc0793598aa5c62d761cb5e17a21e3b
https://hal.univ-grenoble-alpes.fr/hal-02388669
https://hal.univ-grenoble-alpes.fr/hal-02388669
Publikováno v:
8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019)
8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019), 2019, Le Gosier, Guadeloupe, France
HAL
CAMSAP
8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP 2019), 2019, Le Gosier, Guadeloupe, France
HAL
CAMSAP
International audience; Detecting targets embedded in a noisy environment is an important topic in adaptive array processing. In the traditional statistical framework, this problem is addressed through a binary hypothesis test, which usually requires
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7cf093ae066535eb1cea81ea7ec9c1db
https://hal.archives-ouvertes.fr/hal-02292685
https://hal.archives-ouvertes.fr/hal-02292685