Jack William Silverstein

Analysis of the Limiting Spectral Distribution of Large-dimensional General Information-Plus-Noise-Type Matrices

Zhou, H., Hu, J., Bai, Z., & Silverstein, J. W. (2023, July 28). JOURNAL OF THEORETICAL PROBABILITY, Vol. 7.

Limiting eigenvalue behavior of a class of large dimensional random matrices formed from a Hadamard product

Silverstein, J. W. (2022, July 28). RANDOM MATRICES-THEORY AND APPLICATIONS, Vol. 7.

Weak convergence of a collection of random functions defined by the eigenvectors of large dimensional random matrices

RANDOM MATRICES-THEORY AND APPLICATIONS, 11(04).

A tribute to PR Krishnaiah

JOURNAL OF MULTIVARIATE ANALYSIS, 188.

Local Convergence of an AMP Variant to the LASSO Solution in Finite Dimensions

(2020, July 18).

Weak Convergence of a Collection of Random Functions Defined by the Eigenvectors of Large Dimensional Random Matrices

(2020, December 23).

Singular values of large non-central random matrices

Random Matrices: Theory and Applications, 6, 2050012.

The random matrix regime of Maronna's M-estimator with elliptically distributed samples

JOURNAL OF MULTIVARIATE ANALYSIS, 139, 56–78.

A note on the CLT of the LSS for sample covariance matrix from a spiked population model

JOURNAL OF MULTIVARIATE ANALYSIS, 130, 194–207.

Robust Estimates of Covariance Matrices in the Large Dimensional Regime

IEEE TRANSACTIONS ON INFORMATION THEORY, 60(11), 7269–7278.

A joint robust estimation and random matrix framework with application to array processing

2013 IEEE International Conference on Acoustics, Speech and Signal Processing. Presented at the ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Separation of the largest eigenvalues in eigenanalysis of genotype data from discrete subpopulations

THEORETICAL POPULATION BIOLOGY, 89, 34–43.

A CLT FOR INFORMATION-THEORETIC STATISTICS OF NON-CENTERED GRAM RANDOM MATRICES

Random Matrices: Theory and Applications, 01(02), 1150010.

A Deterministic Equivalent for the Analysis of Correlated MIMO Multiple Access Channels

IEEE Transactions on Information Theory, 57(6), 3493–3514.

Eigen-Inference for Energy Estimation of Multiple Sources

Couillet, R., Silverstein, J. W., Bai, Z., & Debbah, M. (2011, April). IEEE TRANSACTIONS ON INFORMATION THEORY, Vol. 57, pp. 2420–2439.

NO EIGENVALUES OUTSIDE THE SUPPORT OF THE LIMITING SPECTRAL DISTRIBUTION OF INFORMATION-PLUS-NOISE TYPE MATRICES

Random Matrices: Theory and Applications, 01(01), 1150004.

Random Matrix Theory

In International Encyclopedia of Statistical Science (pp. 1168–1170).

Eigen-inference for multi-source power estimation

2010 IEEE International Symposium on Information Theory. Presented at the 2010 IEEE International Symposium on Information Theory - ISIT.

Fundamental Limit of Sample Generalized Eigenvalue Based Detection of Signals in Noise Using Relatively Few Signal-Bearing and Noise-Only Samples

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING, 4(3), 468–480.

Spectral Analysis of Large Dimensional Random Matrices

(2nd ed.). New York: Springer.

Asymptotic capacity of multi-user MIMO communications

2009 IEEE Information Theory Workshop. Presented at the 2009 IEEE Information Theory Workshop (ITW 2009).

Rate region of correlated MIMO multiple access channels and broadcast channels

2009 IEEE/SP 15th Workshop on Statistical Signal Processing. Presented at the 2009 IEEE/SP 15th Workshop on Statistical Signal Processing (SSP).

THE STIELTJES TRANSFORM AND ITS ROLE IN EIGENVALUE BEHAVIOR OF LARGE DIMENSIONAL RANDOM MATRICES

In Random Matrix Theory and Its Applications (pp. 1–25).

No eigenvalues outside the support of the limiting empirical spectral distribution of a separable covariance matrix

JOURNAL OF MULTIVARIATE ANALYSIS, 100(1), 37–57.

Analysis of the limiting spectral distribution of large dimensional information-plus-noise type matrices

JOURNAL OF MULTIVARIATE ANALYSIS, 98(6), 1099–1122.

Fundamental Limit of Sample Eigenvalue based Detection of Signals in Colored Noise using Relatively Few Samples

2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers. Presented at the 2007 41st Asilomar conference on Signals, Systems and Computers (ACSSC).

On the signal-to-interference ratio of CDMA systems in wireless communications

ANNALS OF APPLIED PROBABILITY, 17(1), 81–101.

Gaussian fluctuations for non-Hermitian random matrix ensembles

ANNALS OF PROBABILITY, 34(6), 2118–2143.

On the empirical distribution of eigenvalues of large dimensional information-plus-noise-type matrices

JOURNAL OF MULTIVARIATE ANALYSIS, 98(4), 678–694.

Spectral Analysis of Large Dimensional Random Matrices

(1st ed.). New York / Beijing: Springer / Science Press.

Theory of Large Dimensional Random Matrices for Engineers

2006 IEEE Ninth International Symposium on Spread Spectrum Techniques and Applications. Presented at the 2006 IEEE Ninth International Symposium on Spread Spectrum Techniques and Applications.

Eigenvalues of large sample covariance matrices of spiked population models

JOURNAL OF MULTIVARIATE ANALYSIS, 97(6), 1382–1408.

Vowel pre-processing with a neurally based model

ICASSP '77. IEEE International Conference on Acoustics, Speech, and Signal Processing. Presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing.

CLT for linear spectral statistics of large-dimensional sample covariance matrices

Annals of Probability, 32(1A), 553–605.

Large dimensional random matrix theory for signal detection and estimation in array processing

[1992] IEEE Sixth SP Workshop on Statistical Signal and Array Processing, 276–279.

Exact separation of eigenvalues of large dimensional sample covariance matrices

Annals of Probability, 27(3), 1536–1555.

Methodologies in spectral analysis of large dimensional random matrices, a review - Comment: Complements and new developments

Statistica Sinica, 9(3), 667–671.

No eigenvalues outside the support of the limiting spectral distribution of large-dimensional sample covariance matrices

Annals of Probability, 26(1), 316–345.

Analysis of the Limiting Spectral Distribution of Large Dimensional Random Matrices

Journal of Multivariate Analysis, 54(2), 295–309.

On the Empirical Distribution of Eigenvalues of a Class of Large Dimensional Random Matrices

Journal of Multivariate Analysis, 54(2), 175–192.

Strong Convergence of the Empirical Distribution of Eigenvalues of Large Dimensional Random Matrices

Journal of Multivariate Analysis, 55(2), 331–339.

The spectral radii and norms of large dimensional non-central random matrices

Communications in Statistics. Stochastic Models, 10(3), 525–532.

Signal detection via spectral theory of large dimensional random matrices

IEEE Transactions on Signal Processing, 40(8), 2100–2105.

Spectral theory of large dimensional random matrices applied to signal detection

[Technical Report.].

Weak Convergence of Random Functions Defined by The Eigenvectors of Sample Covariance Matrices

The Annals of Probability, 18(3), 1174–1194.

On the eigenvectors of large dimensional sample covariance matrices

Journal of Multivariate Analysis, 30(1), 1–16.

On the weak limit of the largest eigenvalue of a large dimensional sample covariance matrix

Journal of Multivariate Analysis, 30(2), 307–311.

A note on the largest eigenvalue of a large dimensional sample covariance matrix

Journal of Multivariate Analysis, 26(2), 166–168.

Eigenvalues and eigenvectors of large-dimensional sample covariance matrices

Random Matrices and Their Applications, 50, 153–159.

The Limiting Eigenvalue Distribution of a Multivariate F Matrix

SIAM Journal on Mathematical Analysis, 16(3), 641–646.

The Smallest Eigenvalue of a Large Dimensional Wishart Matrix

The Annals of Probability, 13(4), 1364–1368.

Comments on a result of Yin, Bai, and Krishnaiah for large dimensional multivariate F matrices

Journal of Multivariate Analysis, 15(3), 408–409.

On Limit of the Largest Eigenvalue of the Large Dimensional Sample Covariance Matrix.

Some limit theorems on the eigenvectors of large dimensional sample covariance matrices

Journal of Multivariate Analysis, 15(3), 295–324.

A nonlinear system with singular vector field near equilibria

Applicable Analysis, 12(1), 57–71.

Describing the Behavior of Eigenvectors of Random Matrices Using Sequences of Measures on Orthogonal Groups

SIAM Journal on Mathematical Analysis, 12(2), 274–281.

On the Randomness of Eigenvectors Generated from Networks with Random Topologies

SIAM Journal on Applied Mathematics, 37(2), 235–245.

On word classification using a neural network

(Pattern Analysis Report No. 43; Vol. 2; By U. Grenander). Providence, Rhode Island: Division of Applied Mathematics, Brown University.

Public key cryptosystems: an elementary overview

In Confidentiality in Surveys (Report No. 29). Stockholm, Sweden: Department of Statistics, University of Stockholm.

Reply to Grossberg.

Psychological Review, 85(6), 597–603.

Distinctive features, categorical perception, and probability learning: Some applications of a neural model.

Psychological Review, 84(5), 413–451.

Spectral Analysis of Networks with Random Topologies

SIAM Journal on Applied Mathematics, 32(2), 499–519.

Stability analysis and correction of pathological behavior of neural networks

(Pattern Analysis Report No. 48). Providence, Rhode Island: Division of Applied Mathematics, Brown University.

Asymptotics applied to a neural network

Biological Cybernetics, 22(2), 73–84.

Preprocessing with a simple neural model

Neuroscience Abstracts, 2(618), 438.

Comments on ‘A Unitary Transformation Method for Angle-of-Arrival Estimation’

Combettes, P. L., & Silverstein, J. [Technical Report].

Comments on ‘A Unitary Transformation Method for Angle-of-Arrival Estimation’

Combettes, P. L., & Silverstein, J. Comments on ‘A Unitary Transformation Method for Angle-of-Arrival Estimation.’

On the rectification of covariance matrices

Combettes, P. L., & Silverstein, J. [Technical Report].

On the rectification of covariance matrices

Combettes, P. L., & Silverstein, J.