This article presents a new subspace-based technique for reducing the noise of signals in time-series. In the proposed approach, the signal is initially represented as a data matrix. Then using Singular Value Decomposition (SVD), noisy data matrix is divided into signal subspace and noise subspace. In this subspace division, each derivative of the singular values with respect to rank order is u...

In this paper two ways to compute singular values are presented which use Cholesky decomposition as their basic operation.

Let T : H1 H2 H3 ! C be a trilinear form where H1, H2, H3 are separable Hilbertspaces. In the hypothesis that at least two of the three spaces are nite dimensional weshow that the norm square = kTk2 is a root of a certain algebraic equation, usually ofvery high degree, which we baptize the milleniar equation, because it is an analogue ofthe secular equation in the bilinear c...

In this note‎, ‎we obtain some singular values inequalities for positive semidefinite matrices by using block matrix technique‎. ‎Our results are similar to some inequalities shown by Bhatia and Kittaneh in [Linear Algebra Appl‎. ‎308 (2000) 203-211] and [Linear Algebra Appl‎. ‎428 (2008) 2177-2191]‎.

Plates and shells are significant structural components in many engineering and industrial applications. In this study, the free vibration analysis of annular plates is investigated. To this aim, two different numerical methods including the differential quadrature and the discrete singular convolution methods are performedfor numerical simulations. Moreover, the Frequency values are obtained v...

this article presents a new subspace-based technique for reducing the noise ofsignals in time-series. in the proposed approach, the signal is initially representedas a data matrix. then using singular value decomposition (svd), noisy datamatrix is divided into signal subspace and noise subspace. in this subspace division,each derivative of the singular values with respect to rank order is used ...