Low-Rank Approximation of Circulant Matrix to a Noisy Matrix

Author:

Al-Homidan SulimanORCID

Funder

King Fahd University of Petroleum and Minerals

Publisher

Springer Science and Business Media LLC

Subject

Multidisciplinary

Reference16 articles.

1. Andrade, E.; Arrieta, L.; Manzaneda, C.; Robbiano, M.: On the spectra of some $$g$$-circulant matrices and applications to nonnegative inverse eigenvalue problem. Linear Algebra Appl. 590, 1–21 (2020)

2. Xu, J.; Yang, Z.; Jiang, Y.: The best rank-one approximation of a symmetric tensor based on the block circulant matrix. Oper. Res. Trans. 23(1), 53–60 (2019)

3. Olson, B.; Shaw, S.; Shi, C.; Pierre, C.; Parker, R.: Circulant matrices and their application to vibration analysis. Appl. Mech. Rev. (2014). https://doi.org/10.1115/1.4027722

4. Al-Homidan, S.: Computing the nearest circulant positive semi–definite matrix to a noisy matrix. J. Nonlinear Convex Anal. (to appear)

5. Al-Homidan, S.: Low rank methods for solving the nearest correlation matrix problem. J. Nonlinear Convex Anal. 19(6), 881–892 (2018)

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