Truncated singular value decomposition is a reduced version of the in which only few largest values are retained. This paper presents novel perturbation analysis for truncated real matrices. First, we describe expansions truncation order r . We extend results subspace to derive first-order expansion operator about matrix with rank greater than or equal Observing that can be greatly simplified w...

Simultaneous seismic data denoising and reconstruction is a currently popular research subject in modern reflection seismology. Traditional rank-reduction based 3D seismic data denoising and reconstruction algorithm will cause strong residual noise in the reconstructed data and thus affect the following processing and interpretation tasks. In this paper, we propose an improved rank-reduction me...

Gust and turbulence events are of primary importance for the analysis flight incidents, design gust load alleviation systems calculation loads in airframe. cannot be measured directly but they can obtained through direct or optimisation-based methods. In method discretisation Fredholm Integral equation is associated with an ill conditioned matrix. this work effects regularisation methods includ...

In this paper a new dictionary learning algorithm for multidimensional data is proposed. Unlike most conventional dictionary learning methods which are derived for dealing with vectors or matrices, our algorithm, named KTSVD, learns a multidimensional dictionary directly via a novel algebraic approach for tensor factorization as proposed in [3, 12, 13]. Using this approach one can define a tens...

Cortical dipole imaging has been developed to visualize brain electrical activity in high spatial resolution. It is necessary to solve an inverse problem to estimate the cortical dipole distribution from the scalp potentials. In the present study, the accuracy of cortical dipole imaging was improved by focusing on filtering property of the spatial inverse filter. We proposed an inverse filter t...

A hybrid inversion scheme for through-the-wall imaging is proposed in this paper. The approach based on a linearized model of the inverse-scattering problem, employing Green’s function developed layered background. reconstruction obtained by means Landweber-like iterative method performing regularization framework variable-exponent Lebesgue spaces. Thanks to non-conventional geometrical propert...