It is well known that any positive matrix can be scaled to have prescribed row and column sums by multiplying its rows columns certain scaling factors. This procedure as scaling, has found numerous applications in operations research, economics, image processing, machine learning. In this work, we establish the stability of random bounded perturbations. Specifically, letting A˜?RM×N a whose ent...

In this paper, a color image watermarking algorithm based on Redundant Discrete Wavelet Transform (RDWT) and Singular Value Decomposition (SVD) is proposed. The new algorithm selects blue component of a color image to carry the watermark information since the Human Visual System (HVS) is least sensitive to it. To increase the robustness especially towards affine attacks, RDWT is adopted for its...

in bibliometric and scientometric studies, three approaches of multivariate analysis, namely factor analysis, cluster analysis and multidimensional scaling are the most used methods. this article aims to review the use and applications of these techniques.

In [14], Walter and Shen use an Abel summation technique to construct a positive scaling function Pr, 0 < r < 1, from an orthonormal scaling function φ that generates V0. A reproducing kernel can in turn be constructed using Pr. This kernel is also positive, has unit integral, and approximations utilitizing it display no Gibbs’ phenomenon. These results were extended to scaling vectors and mult...

Let be a compactly supported, orthonormal scaling function that generates the linear space V0 2 L2(IR). We are motivated by the work of Walter and Shen [7]. In this paper, the authors use an Abel summation technique to build a positive scaling function Pr, 0 < r < 1, for the space V0. A reproducing kernel can in turn be constructed using Pr. This kernel is also positive, has unit integral, and ...