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Solving interpolation problems via generalized eigenvalue minimization
Solving interpolation problems generalized eigenvalue minimization
2015/7/13
A number of problems in the analysis and design of control systems may be reformulated as the problem of minimizing the largest generalized eigenvalue of a pair of symmetric matrices which depend affi...
Distribution of the largest eigenvalue for real Wishart and Gaussian random matrices and a simple approximation for the Tracy-Widom distribution
Random Matrix Theory characteristic roots largest eigenvalue Tracy-Widom Distribution Wishart Matrices Gaussian Orthogonal Ensemble
2012/11/23
We derive the exact distribution of the largest eigenvalue for finite dimensions real Wishart matrices and for the Gaussian Orthogonal Ensemble (GOE). We compare the exact distribution with the Tracy-...
A perturbative approach to the reconstruction of the eigenvalue spectrum of a normal covariance matrix from a spherically truncated counterpart
A perturbative approach the reconstruction the eigenvalue spectrum a normal covariance matrix a spherically truncated counterpart
2012/9/18
In this paper we propose a perturbative method for the reconstruction of the covariance matrix of a multinormal distribution, under the assumption that the only available information amounts to the co...
A D.C. Programming Approach to the Sparse Generalized Eigenvalue Problem
Generalized eigenvalue problem Principal component analysis Canonicalcorrelation analysis Fisher discriminant analysis
2010/3/17
In this paper, we consider the sparse eigenvalue problem wherein the goal is to obtain a
sparse solution to the generalized eigenvalue problem. We achieve this by constraining the
cardinality of the...
Using the Eigenvalue Relaxation for Binary Least-Squares Estimation Problems
Eigenvalue Relaxation Binary Least-Squares Estimation Problems
2010/3/18
The goal of this paper is to survey the properties of the eigenvalue relaxation for least squares binary problems. This relaxation is a convex program which is obtained as the Lagrangian dual of the o...
Sample eigenvalue based detection of high dimensional signals in white noise using relatively few samples
SSP-DETC Detection SAM-SDET Source detection
2010/4/29
The detection and estimation of signals in noisy, limited data is a problem of interest to many scientific and engineering communities. We present a mathematically justifiable, computationally simple,...