The problem of joint approximate diagonalization of symmetric real matrices is addressed. It is reduced to an optimization problem with the restriction that the matrix of the similarity transformation ...

Abstract: Approximate Joint Diagonalization (AJD) of a set of symmetric matrices by an orthogonal transform is a popular problem in Blind Source Separation (BSS). In this paper we propose a gradient ...

Abstract: A new algorithm for parallel joint diagonalization of symmetric (Hermitian) matrices is introduced. The approach is based on the Jacobi diagonalization, utilizes the distribution of the ...

The diagonalization of matrices may be the top priority in the application of modern physics. In this paper, we numerically demonstrate that, for real symmetric random matrices with non-positive ...

Symmetric matrices of huge size with many zero entries, called sparse symmetric matrices, are nowadays studied actively in the context of artificial intelligence and data science. One of the efficient ...

This is a preview. Log in through your library . Abstract Computationally stable decompositions for skew-symmetric matrices, which take advantage of the skew-symmetry in order to halve the work and ...

This is a preview. Log in through your library . Abstract In this paper we consider estimating the rank of an unknown symmetric matrix based on a symmetric, asymptotically normal estimator of the ...