1 College of Communication Engineering, Jilin University, Changchun 130012, China ([email protected]) 2 School of Electronics and Information Engineering, Shenyang Aerospace University, Shenyang 110136, China Abstract A subspace based speech enhancement algorithm with low complexity is proposed by using our improved subspace iteration method. Due to the use of the iteration, the proposed algorithm ...

We present a numerical method for efficiently detecting unstable periodic orbits (UPO's) embedded in chaotic attractors of high-dimensional systems. This method, which we refer to as subspace fixed-point iteration, locates fixed points of Poincaré maps using a form of fixed-point iteration that splits the phase space into appropriate subspaces. In this paper, among a number of possible implemen...

Iterative algorithms for large-scale eigenpair computation are mostly based subspace projections consisting of two main steps: a subspace update (SU) step that generates bases for approximate eigenspaces, followed by a Rayleigh-Ritz (RR) projection step that extracts approximate eigenpairs. A predominant methodology for the SU step makes use of Krylov subspaces that builds orthonormal bases pie...

GROUSE (Grassmannian Rank-One Update Subspace Estimation) is an iterative algorithm for identifying a linear subspace of Rn from data consisting of partial observations of random vectors from that subspace. This paper examines local convergence properties of GROUSE, under assumptions on the randomness of the observed vectors, the randomness of the subset of elements observed at each iteration, ...

Traditional numerical methods for calculating matrix eigenvalues are prohibitively expensive high-dimensional problems. Iterative random sparsification allow the estimation of a single dominant eigenvalue at reduced cost by leveraging repeated sampling and averaging. We present general approach to extending such multiple demonstrate its performance several benchmark problems in quantum chemistry.

For a square system of analytic equations, a Newton-invariant subspace is a set which contains the resulting point of a Newton iteration applied to each point in the subspace. For example, if the equations have real coefficients, then the set of real points form a Newtoninvariant subspace. Starting with any point for which Newton’s method quadratically converges to a solution, this article uses...