AbstractLet W be a correlated complex non-central Wishart matrix defined through W=XHX, where X is an n×m(n≥m) complex Gaussian with non-zero mean Υ and non-trivial covariance Σ. We derive exact expressions for the cumulative distribution functions (c.d.f.s) of the extreme eigenvalues (i.e., maximum and minimum) of W for some particular cases. These results are quite simple, involving rapidly converging infinite series, and apply for the practically important case where Υ has rank one. We also derive analogous results for a certain class of gamma-Wishart random matrices, for which ΥHΥ follows a matrix-variate gamma distribution. The eigenvalue distributions in this paper have various applications to wireless communication systems, and arise...
Let A(t) be a complex Wishart process defined in terms of the MxN complex Gaussian matrix X(t) by A(...
In multi-channel detection, sufficient statistics for Generalized Likelihood Ratio and Bayesian test...
The beta-Jacobi ensembles complete the triad of ``classical" matrix ensembles (together with Hermite...
Let W be a correlated complex non-central Wishart matrix defined through W = X(H)X, where X is an n ...
This paper derives analytical expressions for the eigenvalues of so-called gamma-Wishart random matr...
This paper derives analytical expressions for the eigenvalues of so-called gamma-Wishart random matr...
In this paper, the distributions of the largest and smallest eigenvalues of complex Wishart matrices...
In this paper we study the distribution of the scaled largest eigenvalue of complex Wishart matrices...
none2noThe study of the statistical distribution of the eigenvalues of Wishart matrices finds applic...
Using a character expansion method, we calculate exactly the eigenvalue density of random matrices o...
Abstract—In this paper we study the distribution of the scaled largest eigenvalue of complex Wishart...
none1noWe derive efficient recursive formulas giving the exact distribution of the largest eigenvalu...
AbstractLet A(t) be a complex Wishart process defined in terms of the M×N complex Gaussian matrix X(...
Abstract. We present explicit formulas for the distributions of the extreme eigenvalues of the compl...
AbstractWe consider non-white Wishart ensembles 1pXΣX*, where X is a p×N random matrix with i.i.d. c...
Let A(t) be a complex Wishart process defined in terms of the MxN complex Gaussian matrix X(t) by A(...
In multi-channel detection, sufficient statistics for Generalized Likelihood Ratio and Bayesian test...
The beta-Jacobi ensembles complete the triad of ``classical" matrix ensembles (together with Hermite...
Let W be a correlated complex non-central Wishart matrix defined through W = X(H)X, where X is an n ...
This paper derives analytical expressions for the eigenvalues of so-called gamma-Wishart random matr...
This paper derives analytical expressions for the eigenvalues of so-called gamma-Wishart random matr...
In this paper, the distributions of the largest and smallest eigenvalues of complex Wishart matrices...
In this paper we study the distribution of the scaled largest eigenvalue of complex Wishart matrices...
none2noThe study of the statistical distribution of the eigenvalues of Wishart matrices finds applic...
Using a character expansion method, we calculate exactly the eigenvalue density of random matrices o...
Abstract—In this paper we study the distribution of the scaled largest eigenvalue of complex Wishart...
none1noWe derive efficient recursive formulas giving the exact distribution of the largest eigenvalu...
AbstractLet A(t) be a complex Wishart process defined in terms of the M×N complex Gaussian matrix X(...
Abstract. We present explicit formulas for the distributions of the extreme eigenvalues of the compl...
AbstractWe consider non-white Wishart ensembles 1pXΣX*, where X is a p×N random matrix with i.i.d. c...
Let A(t) be a complex Wishart process defined in terms of the MxN complex Gaussian matrix X(t) by A(...
In multi-channel detection, sufficient statistics for Generalized Likelihood Ratio and Bayesian test...
The beta-Jacobi ensembles complete the triad of ``classical" matrix ensembles (together with Hermite...