全部 标题 作者
关键词 摘要

OALib Journal期刊
ISSN: 2333-9721
费用:99美元

查看量下载量

相关文章

更多...

Constrained Low Rank Approximation of the Hermitian Nonnegative-Definite Matrix

DOI: 10.4236/alamt.2020.102003, PP. 22-33

Keywords: Low Rank Approximation, Hermitian Matrix, Nonnegative-Definite Matrix, Least Square

Full-Text   Cite this paper   Add to My Lib

Abstract:

In this paper, we consider a constrained low rank approximation problem: \"\", where E is a given complex matrix, p is a positive integer, and is the set of the Hermitian nonnegative-definite least squares solution to the matrix equation \"\". We discuss the range of p and derive the corresponding explicit solution expression of the constrained low rank approximation problem by matrix decompositions. And an algorithm for the problem is proposed and the numerical example is given to show its feasibility.

References

[1]  Chu, M.T., Funderlic, R.E. and Plemmons, R.J. (2003) Structured Low Rank Approximation. Linear Algebra and its Applications, 366, 157-172.
https://doi.org/10.1016/S0024-3795(02)00505-0
[2]  Duan, X.F., Bai, J.C., Zhang, M.J. and Zhang, X.J. (2014) On the Generalized Low Rank Approximation of the Correlation Matrices Arising in the Asset Portfolio. Linear Algebra and its Applications, 461, 1-17.
https://doi.org/10.1016/j.laa.2014.07.026
[3]  Markovsky, I. (2008) Structured Low-Rank Approximation and Its Applications. Automatica, 44, 891-909.
https://doi.org/10.1016/j.automatica.2007.09.011
[4]  Zhang, Z.Y. and Wu, L.X. (2003) Optimal Low-Rank Approximation to a Correlation Matrix. Linear Algebra and its Applications, 364, 161-187.
https://doi.org/10.1016/S0024-3795(02)00551-7
[5]  Li, H.B., Stoica, E.P. and Li, J. (1999) Computationally Efficient Maximum Likelihood Estimation of Structured Covariance Matrices. IEEE Transactions on Signal Processing, 47, 1314-1323.
https://doi.org/10.1109/78.757219
[6]  Williams, D.E. and Johnson, D.H. (1993) Robust Estimation on Structured Covariance Matrices. IEEE Transactions on Signal Processing, 41, 2891-2906.
https://doi.org/10.1109/78.236511
[7]  De Moor, B. (1994) Total Least Squares for Affinely Structured Matrices and the Noisy Realization Problem. IEEE Transactions on Signal Processing, 42, 3104-3113.
https://doi.org/10.1109/78.330370
[8]  Park, H., Lei, Z. and Rosen, J.B. (1999) Low Rank Approximation of a Hankel Matrix by Structured Total Least Norm. BIT Numerical Mathematics, 39, 757-779.
https://doi.org/10.1023/A:1022347425533
[9]  Karmarkar, N.K. and Lakshman, Y.N. (1998) On Approximate GCDs of Unvariate Polynomials. Journal of Symbolic Computation, 26, 653-666.
https://doi.org/10.1006/jsco.1998.0232
[10]  Glunt, W., Hayden, T.L., Hong, S. and Wells, J. (1990) An Alternating Projection Algorithm for Computing the Nearest Euclidean Distance Matrix. SIAM Journal on Matrix Analysis and Applications, 11, 589-600.
https://doi.org/10.1137/0611042
[11]  Fan, J.Y. and Zhou, A.W. (2016) The CP-Matrix Approximation Problem. SIAM Journal on Matrix Analysis and Applications, 37, 171-194.
https://doi.org/10.1137/15M1012086
[12]  Huckle, T., Serra-Capizzano S. and Tablino-Possio, C. (2004) Preconditioning Strategies for Hermitian Indefinite Toeplitz Linear Systems SIAM Journal on Scientific Computing, 25, 1633-1654.
https://doi.org/10.1137/S1064827502416332
[13]  Baksalary, J.K. (1984) Nonnegative Definite and Positive Definite Solutions to the Matrix Equation AXAH=B. Linear and Multilinear Algebra, 16, 133-139.
https://doi.org/10.1080/03081088408817616
[14]  Groβ, J. (2000) Nonnegative-Define and Positive Solutions to the Matrix Equation AXAH=B—Revisited. Linear Algebra and its Applications, 321, 123-129.
https://doi.org/10.1016/S0024-3795(00)00033-1
[15]  Khatri, C.G. and Mitra, S.K. (1976) Hermitian and Nonnegative Definite Solutions of Linear Matrix Equations. SIAM Journal on Applied Mathematics, 31, 579-585.
https://doi.org/10.1137/0131050
[16]  Zhang, X. and Cheng, M. (2003) The Rank-Constrained Hermitian Nonnegative-Definite and Positive-Definite Solutions to the Matrix Equation AXAH=B. Linear Algebra and its Applications, 370, 163-174.
https://doi.org/10.1016/S0024-3795(03)00385-9
[17]  Wei, M.S. and Wang, Q. (2007) On Rank-Constrained Hermitian Nonnegative-Definite Least Squares Solutions to the Matrix Equation AXAH=B. International Journal of Computer Mathematics, 84, 945-952.
https://doi.org/10.1080/00207160701458344
[18]  Liu, X.F., Li, W. and Wang, H.X. (2017) Rank Constrained Matrix Best Approximation Problem with Respect to (Skew) Hermitian Matrices. Journal of Computational and Applied Mathematics, 319, 77-86.
https://doi.org/10.1016/j.cam.2016.12.029
[19]  Wei, M. and Shen, D. (2012) Minimum Rank Solutions to the Matrix Approximation Problems in the Spectral Norm. SIAM Journal on Matrix Analysis and Applications, 33, 940-957.
https://doi.org/10.1137/110851134
[20]  Shen, D., Wei, M. and Liu, Y. (2015) Minimum Rank (Skew) Hermitian Solutions to the Matrix Approximation Problem in the Spectral Norm. Journal of Computational and Applied Mathematics, 288, 351-365.
https://doi.org/10.1016/j.cam.2015.04.033
[21]  Zhang, F.Z. (1999) Matrix Theory: Basic Results and Techniques. Springer, New York.
[22]  Albert, A. (1969) Condition for Positive and Nonnegative Definite in Terms of Pseudoinverse. SIAM Journal on Applied Mathematics, 17, 434-440.
https://doi.org/10.1137/0117041

Full-Text

comments powered by Disqus

Contact Us

service@oalib.com

QQ:3279437679

WhatsApp +8615387084133

WeChat 1538708413