Jack W Silverstein

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Romain COUILLETUGA IDEX DataScience Chair, GIPSA-lab, University Grenoble-AlpesVerified email at gipsa-lab.grenoble-inp.fr
Merouane DebbahKU 6G Center, Khalifa University, CentralesupelecVerified email at centralesupelec.fr
Frédéric PascalProfessor, L2S/CentraleSupélecVerified email at centralesupelec.fr
Jinho BaikDepartment of Mathematics, University of MichiganVerified email at umich.edu
Raj Rao NadakuditiAssociate Professor, University of MichiganVerified email at umich.edu
Patrick L. CombettesDepartment of Mathematics, North Carolina State UniversityVerified email at math.ncsu.edu
Debashis PaulUniversity of California, Davis and Indian Statistical Instititute, KolkataVerified email at ucdavis.edu
Wlodek BrycProfessor of Mathematical Sciences, University of CincinnatiVerified email at uc.edu
Brian RiderProfessor, Temple UniversityVerified email at temple.edu
Jamal NajimCNRS et Université Gustave Eiffel (Paris Est)Verified email at univ-eiffel.fr
Jianfeng (Jeff) YaoThe Chinese University of Hong Kong (Shenzhen)Verified email at cuhk.edu.cn
Qinwen WANGFudan UniversityVerified email at fudan.edu.cn
Antonia Maria TulinoUniverisità Federico II, Napoli, Italy - New York University, NY USA, - Bell Labs, NJ, USAVerified email at unina.it
Jiang HuNortheast Normal UniversityVerified email at nenu.edu.cn
James AndersonProfessor of Agronomy & Plant Genetics, University of MinnesotaVerified email at umn.edu
Yanting MaMitsubishi Electric Research LaboratoriesVerified email at merl.com
Dror BaronNorth Carolina State UniversityVerified email at ncsu.edu
Min KangDepartment of Mathematics, North Carolina State UniversityVerified email at ncsu.edu
Katarzyna (Kasia) BrycSenior Scientist, Population Genetics

Jack W Silverstein

North Carolina State University

Verified email at math.ncsu.edu - Homepage

Random matrices


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Spectral analysis of large dimensional random matrices Z Bai, JW Silverstein Springer, 2010	2244	2010
Distinctive features, categorical perception, and probability learning: Some applications of a neural model. JA Anderson, JW Silverstein, SA Ritz, RS Jones Psychological review 84 (5), 413, 1977	1437	1977
On the empirical distribution of eigenvalues of a class of large dimensional random matrices JW Silverstein, ZD Bai Journal of Multivariate analysis 54 (2), 175-192, 1995	884	1995
Eigenvalues of large sample covariance matrices of spiked population models J Baik, JW Silverstein Journal of multivariate analysis 97 (6), 1382-1408, 2006	831	2006
CLT for linear spectral statistics of large-dimensional sample covariance matrices ZD Bai, JW Silverstein Advances In Statistics, 281-333, 2008	675	2008
No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices ZD Bai, JW Silverstein The Annals of Probability 26 (1), 316-345, 1998	660	1998
Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices JW Silverstein Journal of Multivariate Analysis 55 (2), 331-339, 1995	614	1995
Analysis of the limiting spectral distribution of large dimensional random matrices JW Silverstein, SI Choi Journal of Multivariate Analysis 54 (2), 295-309, 1995	390	1995
The smallest eigenvalue of a large dimensional Wishart matrix JW Silverstein The Annals of Probability, 1364-1368, 1985	345	1985
A deterministic equivalent for the analysis of correlated MIMO multiple access channels R Couillet, M Debbah, JW Silverstein IEEE Transactions on Information Theory 57 (6), 3493-3514, 2011	229	2011
A note on the largest eigenvalue of a large dimensional sample covariance matrix ZD Bai, JW Silverstein, YQ Yin Journal of Multivariate Analysis 26 (2), 166-168, 1988	223	1988
Fundamental limit of sample generalized eigenvalue based detection of signals in noise using relatively few signal-bearing and noise-only samples RR Nadakuditi, JW Silverstein IEEE Journal of selected topics in Signal Processing 4 (3), 468-480, 2010	187	2010
On the empirical distribution of eigenvalues of large dimensional information-plus-noise-type matrices RB Dozier, JW Silverstein Journal of Multivariate Analysis 98 (4), 678-694, 2007	183	2007
Exact separation of eigenvalues of large dimensional sample covariance matrices ZD Bai, JW Silverstein Annals of probability, 1536-1555, 1999	176	1999
Spectral analysis of networks with random topologies U Grenander, JW Silverstein SIAM Journal on Applied Mathematics 32 (2), 499-519, 1977	130	1977
No eigenvalues outside the support of the limiting empirical spectral distribution of a separable covariance matrix D Paul, JW Silverstein Journal of Multivariate Analysis 100 (1), 37-57, 2009	105	2009
Signal detection via spectral theory of large dimensional random matrices JW Silverstein, PL Combettes IEEE Transactions on Signal Processing 40 (8), 2100-2105, 1992	102	1992
The random matrix regime of Maronna’s M-estimator with elliptically distributed samples R Couillet, F Pascal, JW Silverstein Journal of Multivariate Analysis 139, 56-78, 2015	87	2015
Weak convergence of random functions defined by the eigenvectors of sample covariance matrices JW Silverstein The Annals of Probability, 1174-1194, 1990	87	1990
Analysis of the limiting spectral distribution of large dimensional information-plus-noise type matrices RB Dozier, JW Silverstein Journal of Multivariate Analysis 98 (6), 1099-1122, 2007	79	2007

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