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eess.SP2026
The Gaussian data assumption does not always lead to the largest CRB
Jean-Pierre Delmas, Habti Abeida
This lecture note addresses the common misconception that the Gaussian distribution always yields the largest Cramér-Rao Bound (CRB). We show that this property only holds under re…
eess.SP2019★ 19 cited
Slepian-Bangs formula and Cramer Rao bound for circular and non-circular complex elliptical symmetric distributions
Habti Abeida, Jean-Pierre Delmas
This paper is mainly dedicated to an extension of the Slepian-Bangs formula to non-circular complex elliptical symmetric (NC-CES) distributions, which is derived from a new stochas…
eess.SP2018★ 83 cited
Iterative Sparse Asymptotic Minimum Variance Based Approaches for Array Processing
Habti Abeida, Qilin Zhang, Jian Li +1
This paper presents a series of user parameter-free iterative Sparse Asymptotic Minimum Variance (SAMV) approaches for array processing applications based on the asymptotically min…