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Communication Dans Un Congrès Année : 2020

Efficient Estimation of Kronecker Product of Linear Structured Scatter Matrices under t-distribution

Résumé

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 many applications, such as MIMO communication , MEG/EEG data analysis. Taking this prior knowledge into account generally improves estimation accuracy. In the framework of robust estimation, the t-distribution is particularly suited to model heavy-tailed data. In this context, we introduce an estimator of the scatter matrix, having a Kronecker product structure and potential linear structured factors. In addition, we show that the proposed method yields a consistent and efficient estimate.
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Dates et versions

hal-02873816 , version 1 (18-06-2020)

Identifiants

Citer

Bruno Meriaux, Chengfang Ren, Arnaud Breloy, Mohammed Nabil El Korso, Philippe Forster. Efficient Estimation of Kronecker Product of Linear Structured Scatter Matrices under t-distribution. 28th European Signal Processing Conference (EUSIPCO 2020), Jan 2021, Amsterdam, Netherlands. ⟨10.23919/eusipco47968.2020.9287415⟩. ⟨hal-02873816⟩
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