Jack Silverstein
Jack Silverstein
Zweryfikowany adres z math.ncsu.edu - Strona główna
Tytuł
Cytowane przez
Cytowane przez
Rok
Spectral analysis of large dimensional random matrices
Z Bai, JW Silverstein
Springer, 2010
16142010
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
12931977
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
7801995
Eigenvalues of large sample covariance matrices of spiked population models
J Baik, JW Silverstein
Journal of multivariate analysis 97 (6), 1382-1408, 2006
6632006
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
5661998
CLT for linear spectral statistics of large-dimensional sample covariance matrices
ZD Bai, JW Silverstein
Advances In Statistics, 281-333, 2008
5422008
Strong convergence of the empirical distribution of eigenvalues of large dimensional random matrices
JW Silverstein
Journal of Multivariate Analysis 55 (2), 331-339, 1995
5071995
Analysis of the limiting spectral distribution of large dimensional random matrices
JW Silverstein, SI Choi
Journal of Multivariate Analysis 54 (2), 295-309, 1995
3221995
The smallest eigenvalue of a large dimensional Wishart matrix
JW Silverstein
The Annals of Probability, 1364-1368, 1985
3121985
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
1831988
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
1802011
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
1582007
Exact separation of eigenvalues of large dimensional sample covariance matrices
ZD Bai, JW Silverstein
The Annals of Probability 27 (3), 1536-1555, 1999
1541999
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
1472010
Spectral analysis of networks with random topologies
U Grenander, JW Silverstein
SIAM Journal on Applied Mathematics 32 (2), 499-519, 1977
1221977
Signal detection via spectral theory of large dimensional random matrices
JW Silverstein, PL Combettes
IEEE Transactions on Signal Processing 40 (8), 2100-2105, 1992
1001992
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
802015
Robust estimates of covariance matrices in the large dimensional regime
R Couillet, F Pascal, JW Silverstein
IEEE Transactions on Information Theory 60 (11), 7269-7278, 2014
79*2014
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
782009
Eigenvalues and eigenvectors of large dimensional sample covariance matrices
JW Silverstein
Contemporary Mathematics 50, 153-159, 1986
761986
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