Abstract : A new algorithm for noise filtering, based on non-linear processing of image in blocks, using singular value decomposition (SVD) is presented in this paper. Noise filtering is performed in the domain of singular values and singular vectors. A priori noise variance knowledge is not required, because a singular value-based noise variance estimation is performed in the first phase of th...

Parallel manipulators which are singular with respect to the Schönflies motion group X(a) are called Schönflies-singular, or more precisely X(a)-singular, where a denotes the direction of the rotary axis. A special class of such manipulators are architecturally singular ones because they are singular with respect to any Schönflies group. Another remarkable set of Schönfliessingular planar paral...

other fields. However, the spectral properties of the Laplace Transform tend to complicate its numerical treatment; therefore, the closely related “Truncated” Laplace Transforms are often used in applications. We have constructed efficient algorithms for the evaluation of the left singular functions and singular values of the Truncated Laplace Transform. Together with the previously introduced ...

The computation (or approximation) of some of the smallest or largest singular values of a large sparse matrix is a big challenge, having many important applications. In this talk we discuss approximations to singular triples that can be obtained from subspaces. One of the topics is the concept of harmonic singular triples, introduced in [1]. The word “harmonic” expresses the fact that we try t...

A vector autoregression is singular when explosive characteristic roots have geometric multiplicity larger than one. The singular component is a mixingale. Martingale decompositions are constructed for sample moments involving the singular component. This permits weak and strong analysis in the case of martingale difference innovations. While least squares estimators are shown to be inconsisten...

For the accurate approximation of the minimal singular triple (singular value and left and right singular vector), we may use two separate search spaces, one for the left, and one for the right singular vector. In Lanczos bidiagonalization, for example, such search spaces are constructed. In [3], the author proposes a Jacobi–Davidson type method for the singular value problem, where solutions t...

In this paper we introduce a special form of symmetric matrices that is called central symmetric $X$-form matrix and study some properties, the inverse eigenvalue problem and inverse singular value problem for these matrices.

‎Let $A_{i},B_{i},X_{i},i=1,dots,m,$ be $n$-by-$n$ matrices such that $‎sum_{i=1}^{m}leftvert A_{i}rightvert ^{2}$ and $‎sum_{i=1}^{m}leftvert B_{i}rightvert ^{2}$  are nonzero matrices and each $X_{i}$ is‎ ‎positive semidefinite‎. ‎It is shown that if $f$ is a nonnegative increasing ‎convex function on $left[ 0,infty right) $ satisfying $fleft( 0right)‎ ‎=0 $‎, ‎then  $$‎2s_{j}left( fleft( fra...

In this paper, the singular LR fuzzy linear system is introduced. Such systems are divided into two parts: singular consistent LR fuzzy linear systems and singular inconsistent LR fuzzy linear systems. The capability of the generalized inverses such as Drazin inverse, pseudoinverse, and {1}-inverse in finding minimal solution of singular consistent LR fuzzy linear systems is investigated.