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In this paper, we have introduced a general framework for estimation in the presence of unknown linear nuisance parameters.
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All the estimators designed for CFO estimation in the presence of I/ Qmismatch, showed robustness to I/ Qmismatch in the experiments.
We discuss the asymptotic Cramer-Rao bound (CRB) for frequency estimation in the presence of multiplicative noise.
Finally, an asymptotic closed form CRB for frequency estimation in the presence of multiplicative and additive colored noise is derived.
In this article, we propose a new hybrid algorithm for 2D DOA estimation in the presence of mutual coupling for sparse UCAs.
Powerful schemes for accurate channel estimation in the presence of phase noise have been proposed in [20 22].
We estimated the SEM in (12)–(13) using a feasible efficient two-step GMM procedure for robust covariance estimation in the presence of heteroskedasticity [26] using EViews 9.
Xie et al. [5] provide a hybrid approach for 2D direction-of-arrival estimation in the presence of mutual coupling across the array.
For such UCAs, we propose a new hybrid approach for 2D direction-of-arrival (DOA) estimation in the presence of mutual coupling.
In summary, advances in algorithmic strategies for coalescent-based estimation can enable highly accurate species tree estimation in the presence of massive ILS.
CFO estimation in the presence of I/ Qmismatch is not trivial, and has been investigated in, for example, [5 14].
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