The blind separation of multiple co-channel binary digital signals using an antenna array involves finding a factorization of a data matrix X into X AS, where all entries of S are 1 or −1. It is shown that this problem can be solved exactly and non-iteratively, via a certain generalized eigenvalue decomposition. As indicated by simulations, the algorithm is robust in the presence of noise. An i...

Most computational work in Jacobi-Davidson [9], an iterative method for large scale eigenvalue problems, is due to a so-called correction equation. In [5] a strategy for the approximate solution of the correction equation was proposed. This strategy is based on a domain decomposition preconditioning technique in order to reduce wall clock time and local memory requirements. This report discusse...

By defining two important terms called basic perturbation vectors and obtaining their linear bounds, we obtain the componentwise bounds for unitary factors upper triangular of generalized Schur decomposition. The diagonal elements invariant subspace are also derived. From former, present an bound a condition number eigenvalue. Furthermore, with numerical iterative method, nonlinear decompositio...

In this paper, two adaptive algorithms are presented for robust time delay estimation (TDE) in acoustic environments where a large amount of background noise and reverberation is present. Recently, an adaptive eigenvalue decomposition (EVD) algorithm has been developed for TDE between two microphones in highly reverberant acoustic environments. In this paper, we extend the adaptive EVD algorith...

Three complementary methods have been implemented in the code Denovo that accelerate neutral particle transport calculations with methods that use leadership-class computers fully and effectively: a multigroup block (MG) Krylov solver, a Rayleigh Quotient Iteration (RQI) eigenvalue solver, and a multigrid in energy (MGE) preconditioner. The MG Krylov solver converges more quickly than Gauss Sei...

INTRODUCTION The diffusion tensor is a 3x3 positive definite matrix and, therefore, possesses several distinct matrix decompositions, e.g. the Cholesky, and the Eigenvalue decompositions. To date, the Eigenvalue decomposition has been used only in computing tensor-derived quantities [1-4] but not as a parametrization (or equivalently, a representation) in DTI error propagation [5]. Treating a m...

In this paper, a successive supersymmetric rank-1 decomposition of a real higher-order supersymmetric tensor is considered. To obtain such a decomposition, we design a greedy method based on iteratively computing the best supersymmetric rank-1 approximation of the residual tensors. We further show that a supersymmetric canonical decomposition could be obtained when the method is applied to an o...

In this paper we study mathematically the eigenvalue problem for stochastic elliptic partial differential equation of Wick type. Using the Wick-product and the Wiener-Itô chaos expansion, the stochastic eigenvalue problem is reformulated as a system of an eigenvalue problem for a deterministic partial differential equation and elliptic partial differential equations by using the Fredholm altern...

A modal decomposition strategy based on state-variable ensembles is formulated. A nonsymmetric, generalized eigenvalue problem is constructed. The data-based eigenvalue problem is related to the generalized eigenvalue problem associated with free-vibration solutions of the state-variable formulation of linear multi-degree-of-freedom systems. For linear free-response data, the inverse-transpose ...