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- XUZHOU CHEN, MOODY T CHU
- 1996

An inverse eigenvalue problem, where a matrix is to be constructed from some or all of its eigenvalues, may not have a r e a l-v alued solution at all. An approximate solution in the sense of least squares is sometimes desirable. Two t ypes of least squares problems are formulated and explored in this paper. In spite of their diierent appearance, the two… (More)

- Xuzhou Chen, Jun Ji
- American J. Computational Mathematics
- 2011

This paper presents a recursive procedure to compute the Moore-Penrose inverse of a matrix A. The method is based on the expression for the Moore-Penrose inverse of rank-one modified matrix. The computational complexity of the method is analyzed and a numerical example is included. A variant of the algorithm with lower computational complexity is also… (More)

- Xuzhou Chen, Yan Luo, Jie Wang
- 2012 Fourth International Conference on…
- 2012

A major challenge in virtual network embedding is to find an efficient mapping of each virtual network (VN) to the nodes and links in the substrate network (SN) so that the residual SN can host as many VN requests as possible. This network optimization problem has been shown to be NP hard. In this paper we propose a “border matching” mechanism… (More)

- Xuzhou Chen, Robert E. Hartwig
- Numerical Lin. Alg. with Applic.
- 2005

The semi-iterative method (SIM) was originally inspired by the classical theory of summation and has been discussed by numerous authors [1–4]. In particular, Eiermann, Niethammer and Varga discussed the SIMs for non-singular systems of linear equations. An asymptotically optimal SIM with respect to a certain compact set of C was described. It was further… (More)

- Yan Luo, Xuzhou Chen, Jie Wang
- JNW
- 2013

—How to efficiently map the nodes and links in a given virtual network (VN) to those in the substrate network (SN) so that the residual substrate network (RSN) can host as many VN requests as possible is a major challenge in virtual network embedding. Most research has developed heuristic algorithms with interactive or two-stage methods. These methods,… (More)

- Xuzhou Chen, Nadimpalli V. R. Mahadev
- SIGCSE
- 2012

In this paper, we describe an approach of using a PC based robot (PCRob) for teaching advanced topic course in pattern recognition and computer vision. Unlike most of the robots where only the microprocessors are used, the robot we design and build uses mini PC and off-the-shelf peripherals to provide the computing power in order to process some… (More)

- XUZHOU CHEN, JUN JI
- 2011

In this paper, we study the Moore-Penrose inverse of a symmetric rank-one perturbed matrix from which a finite method is proposed for the minimum-norm least-squares solution to the system of linear equations Ax = b. This method is guaranteed to produce the required result.

- Lu He, Yan Luo, +4 authors Seung Woo Son
- 2015 IEEE High Performance Extreme Computing…
- 2015

Singular value decomposition (SVD) is one of the most important factorizations in matrix computation. However, computing SVD is still time-consuming, especially when the dimension of matrices exceeds tens of thousands. In this paper, we present a high performance approach called “Bisection and Twisted” (BT) for solving bidiagonal SVD. As… (More)

- Xuzhou Chen, Robert E. Hartwig
- American J. Computational Mathematics
- 2011

For an invertible diagonal matrix D , the convergence of the power scaled matrix sequence N N D A is investigated. As a special case, necessary and sufficient conditions are given for the convergence of N N D T , where T is triangular. These conditions involve both the spectrum as well as the diagraph of the matrix T. The results are then used to… (More)

- Jun Ji, Xuzhou Chen
- Applied Mathematics and Computation
- 2014