In this paper, we introduce subspace-frequently hypercyclic operators. We show that these operators are subspace-hypercyclic and there are subspace-hypercyclic  operators that are not subspace-frequently hypercyclic. There is a criterion like to subspace-hypercyclicity criterion that implies subspace-frequent hypercyclicity and if an operator $T$ satisfies this criterion, then $Toplus T$ is sub...

In this paper, we propose a class of fast sequential bi-iteration singular value (Bi-SVD) subspace tracking algorithms for adaptive eigendecomposition of the cross covariance matrix in the recursive instrumental variable (RIV) method of system identification. These algorithms can be used for RIV subspace processing of signals in unknown correlated Gaussian noise. Realizations with O(Nr) and O(N...

When dealing with quantum many-body systems one is faced with problems growing exponentially in the number of particles to be considered. To overcome this curse of dimensionality one has to consider representation formats which scale only polynomially. Physicists developed concepts like matrix product states (MPS) to represent states of interest and formulated algorithms such as the density mat...

Stationary inner iterations in combination with Krylov subspace methods are proposed for least squares problems. The inner iterations are efficient in terms of computational work and memory, and serve as powerful preconditioners also for ill-conditioned and rank-deficient least squares problems. Theoretical justifications for using the inner iterations as preconditioners are presented. Numerica...

The rational QZ method generalizes the by implicitly supporting subspace iteration. In this paper we extend introducing shifts and poles of higher multiplicity in Hessenberg pencil, which is a pencil consisting two matrices. result multishift, multipole iteration on block pencils allows one to stick real arithmetic for input pencil. combination with optimally packed aggressive early deflation a...

We study random eigenvalue problems in the context of spectral stochastic finite elements. In particular, given a parameter-dependent, symmetric positive-definite matrix operator, we explore the performance of algorithms for computing its eigenvalues and eigenvectors represented using polynomial chaos expansions. We formulate a version of stochastic inverse subspace iteration, which is based on...

Earlier this decade, the so-called FEAST algorithm was released for computing the eigenvalues of a matrix in a given interval. Previously, rational filter functions have been examined as a parameter of FEAST. In this thesis, we expand on existing work with the following contributions: (i) Obtaining well-performing rational filter functions via standard minimisation algorithms, (ii) Obtaining co...

Article history: Received 29 December 2016 Accepted 19 February 2017 Available online 29 March 2017