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Daniel Pérez Palomar
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Publications
- 2024
- [c115]Jasin Machkour, Arnaud Breloy, Michael Muma, Daniel P. Palomar, Frédéric Pascal:
Sparse PCA with False Discovery Rate Controlled Variable Selection. ICASSP 2024: 9716-9720 - [i43]Jasin Machkour, Arnaud Breloy, Michael Muma, Daniel P. Palomar, Frédéric Pascal:
Sparse PCA with False Discovery Rate Controlled Variable Selection. CoRR abs/2401.08375 (2024) - 2023
- [j115]Esa Ollila, Daniel P. Palomar, Frédéric Pascal:
Affine Equivariant Tyler's M-Estimator Applied to Tail Parameter Learning of Elliptical Distributions. IEEE Signal Process. Lett. 30: 1017-1021 (2023) - 2021
- [j111]Esa Ollila, Daniel P. Palomar, Frédéric Pascal:
Shrinking the Eigenvalues of M-Estimators of Covariance Matrix. IEEE Trans. Signal Process. 69: 256-269 (2021) - [c99]Frédéric Pascal, Esa Ollila, Daniel P. Palomar:
Improved estimation of the degree of freedom parameter of multivariate $t$-distribution. EUSIPCO 2021: 860-864 - 2020
- [c95]Esa Ollila, Daniel P. Palomar, Frédéric Pascal:
M-Estimators of Scatter with Eigenvalue Shrinkage. ICASSP 2020: 5305-5309 - 2016
- [j82]Ying Sun, Arnaud Breloy, Prabhu Babu, Daniel P. Palomar, Frédéric Pascal, Guillaume Ginolhac:
Low-Complexity Algorithms for Low Rank Clutter Parameters Estimation in Radar Systems. IEEE Trans. Signal Process. 64(8): 1986-1998 (2016) - [c67]Arnaud Breloy, Ying Sun, Prabhu Babu, Guillaume Ginolhac, Daniel Pérez Palomar, Frédéric Pascal:
A robust signal subspace estimator. SSP 2016: 1-4
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last updated on 2024-09-13 01:36 CEST by the dblp team
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