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1
ABORT-Like Detectors: A Bayesian Approach
ABORT-Like Detectors: A Bayesian Approach
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ABORT-Like Detectors: A Bayesian Approach

Bandiera, Francesco ; Besson, Olivier ; Coluccia, Angelo ; Ricci, Giuseppe

IEEE transactions on signal processing, 2015-10, Vol.63 (19), p.5274-5284 [Periódico revisado por pares]

IEEE

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2
Accurate and Computationally Efficient Tensor-Based Subspace Approach for Multidimensional Harmonic Retrieval
Accurate and Computationally Efficient Tensor-Based Subspace Approach for Multidimensional Harmonic Retrieval
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Accurate and Computationally Efficient Tensor-Based Subspace Approach for Multidimensional Harmonic Retrieval

Weize Sun ; So, H. C.

IEEE transactions on signal processing, 2012-10, Vol.60 (10), p.5077-5088 [Periódico revisado por pares]

New York, NY: IEEE

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3
Active power minimization of a sound source in a reverberant closed space
Active power minimization of a sound source in a reverberant closed space
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Active power minimization of a sound source in a reverberant closed space

Tohyama, M. ; Suzuki, A. ; Sugiyama, K.

IEEE transactions on signal processing, 1991-01, Vol.39 (1), p.246-248 [Periódico revisado por pares]

IEEE

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4
Activity Detection for Massive Connectivity in Cell-Free Networks With Unknown Large-Scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach
Activity Detection for Massive Connectivity in Cell-Free Networks With Unknown Large-Scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach
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Activity Detection for Massive Connectivity in Cell-Free Networks With Unknown Large-Scale Fading, Channel Statistics, Noise Variance, and Activity Probability: A Bayesian Approach

Zhang, Hao ; Lin, Qingfeng ; Li, Yang ; Cheng, Lei ; Wu, Yik-Chung

IEEE transactions on signal processing, 2024, Vol.72, p.942-957 [Periódico revisado por pares]

New York: IEEE

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5
Adaptation and Learning Over Networks Under Subspace Constraints-Part II: Performance Analysis
Adaptation and Learning Over Networks Under Subspace Constraints-Part II: Performance Analysis
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Adaptation and Learning Over Networks Under Subspace Constraints-Part II: Performance Analysis

Nassif, Roula ; Vlaski, Stefan ; Sayed, Ali H.

IEEE transactions on signal processing, 2020, Vol.68, p.2948-2962 [Periódico revisado por pares]

New York: IEEE

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6
Adaptation dynamics of the spherical subspace tracker
Adaptation dynamics of the spherical subspace tracker
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Adaptation dynamics of the spherical subspace tracker

Dowling, E.M. ; DeGroat, R.D.

IEEE transactions on signal processing, 1992-10, Vol.40 (10), p.2599-2602 [Periódico revisado por pares]

NEW YORK: IEEE

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7
Adaptive convergence of linearly constrained beamformers based on the sample covariance matrix
Adaptive convergence of linearly constrained beamformers based on the sample covariance matrix
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Adaptive convergence of linearly constrained beamformers based on the sample covariance matrix

Van Veen, B.D.

IEEE transactions on signal processing, 1991-06, Vol.39 (6), p.1470-1473 [Periódico revisado por pares]

IEEE

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8
Adaptive Detection and Estimation in the Presence of Useful Signal and Interference Mismatches
Adaptive Detection and Estimation in the Presence of Useful Signal and Interference Mismatches
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Adaptive Detection and Estimation in the Presence of Useful Signal and Interference Mismatches

De Maio, A. ; De Nicola, S. ; Yongwei Huang ; Shuzhong Zhang ; Farina, A.

IEEE transactions on signal processing, 2009-02, Vol.57 (2), p.436-450 [Periódico revisado por pares]

New York, NY: IEEE

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9
Adaptive Detection in Gaussian Interference With Unknown Covariance After Reduction by Invariance
Adaptive Detection in Gaussian Interference With Unknown Covariance After Reduction by Invariance
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Adaptive Detection in Gaussian Interference With Unknown Covariance After Reduction by Invariance

De Maio, Antonio ; Conte, Ernesto

IEEE transactions on signal processing, 2010-06, Vol.58 (6), p.2925-2934 [Periódico revisado por pares]

New York, NY: IEEE

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10
Adaptive Detection of a Signal Known Only to Lie on a Line in a Known Subspace, When Primary and Secondary Data are Partially Homogeneous
Adaptive Detection of a Signal Known Only to Lie on a Line in a Known Subspace, When Primary and Secondary Data are Partially Homogeneous
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Adaptive Detection of a Signal Known Only to Lie on a Line in a Known Subspace, When Primary and Secondary Data are Partially Homogeneous

Besson, O. ; Scharf, L.L. ; Kraut, S.

IEEE transactions on signal processing, 2006-12, Vol.54 (12), p.4698-4705 [Periódico revisado por pares]

New York, NY: IEEE

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