Skip to main content
Log in

Determinants and inverses of weighted Loeplitz and weighted Foeplitz matrices and their applications in data encryption

  • Original Research
  • Published:
Journal of Applied Mathematics and Computing Aims and scope Submit manuscript

Abstract

In this paper, we investigate the analytical determinants and inverses of \(n\times n\) weighted Loeplitz and weighted Foeplitz matrices. We introduce the \(n\times n\) weighted Loeplitz and weighted Foeplitz matrices and derive the analytical determinants and inverses of them by constructing the transformation matrices. Specifically, we can use the nth, \((n+1)\)st and \((n+2)\)th Fibonacci numbers to express the analytical inverse of the \(n\times n\) weighted Loeplitz matrix which is sparse. We also present the analytical determiants and inverses of the \(n\times n\) weighted Lankel and weighted Fankel matrices. Finally, we give two application examples of the main results in data and image encryption.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Barnabei, M., Guerrini, C., Montefusco, L.B.: Some algebraic aspects of signal processing. Linear Algebra Appl. 284(1–3), 3–17 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  2. Zeng, M.L.: A circulant-matrix-based new accelerated GSOR preconditioned method for block two-by-two linear systems from image restoration problems. Appl. Numer. Math. 164(20), 245–257 (2021)

    Article  MathSciNet  MATH  Google Scholar 

  3. Krueger, K., Mcclellan, J. H., Scott, W. R.: 3-D imaging for ground penetrating radar using compressive sensing with block-toeplitz structures. In: IEEE 7th Conference: Sensor Array & Multichannel Signal Processing Workshop, 229–232 (2012)

  4. Sathik, M.M., Sujatha, S.S.: Application of Toeplitz matrix in watermarking for image authentication. In: 2011 International Conference on Computer, Communication and Electrical Technology (ICCCET), 55–59. https://doi.org/10.1109/ICCCET.2011.5762438. (2011)

  5. Costarelli, D., Seracini, M., Vinti, G.: A comparison between the sampling Kantorovich algorithm for digital image processing with some interpolation and quasi-interpolation methods. Appl. Math. Comput. 374, 125046 (2020)

    MathSciNet  MATH  Google Scholar 

  6. Wu, Y., Fang, Y., Fan, Z., Wang, C., Liu, C.: An automated vertical drift correction algorithm for AFM images based on morphology prediction. Micron 140, 102950 (2021)

    Article  Google Scholar 

  7. Saeed, K.: Carathéodory-Toeplitz based mathematical methods and their algorithmic applications in biometric image processing. Appl. Numer. Math. 75, 2–21 (2014)

    Article  MATH  Google Scholar 

  8. Liao, L.D., Zhang, G.F.: New variant of the HSS iteration method for weighted Toeplitz regularized least-squares problems from image restoration. Comput. Math. Appl. 73(11), 2482–2499 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  9. Marivani, I., Tsiligianni, E., Cornelis, B., Deligiannis, N.: Multimodal deep unfolding for guided image super-resolution. IEEE Trans. Image Process. 29, 8443–8456 (2020)

    Article  MATH  Google Scholar 

  10. Liu, J., Ni, A., Ni, G.: A nonconvex \(l_1(l_1-l_2)\) model for image restoration with impulse noise. J. Comput. Appl. Math. 378, 112934 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  11. Liu, Y., Wang, A., Zhou, H., Jia, P.: Single nighttime image dehazing based on image decomposition. Signal Process. 183(5), 107986 (2021)

    Article  Google Scholar 

  12. Wu, Y.H., Song, W.R., Zheng, J.Y., Liu, F.: Non-uniform low-light image enhancement via non-local similarity decomposition model. Signal Process. Image Commun. 93(2), 116141 (2021)

    Article  Google Scholar 

  13. Shang, X.L., Li, J., Stoica, P.: Weighted SPICE algorithms for range-doppler imaging using one-bit automotive radar. IEEE J. Sel. Top. Signal Process. 15(4), 1041–1054 (2021)

    Article  Google Scholar 

  14. Jiang, Z.L., Gong, Y.P., Gao, Y.: Invertibility and explicit inverses of circulant-type matrices with \(k\)-Fibonacci and \(k\)-Lucas number. Abstr. Appl. Anal. 2014, 238953 (2014)

    MathSciNet  MATH  Google Scholar 

  15. Zheng, Y.P., Shon, S.: Exact determinants and inverses of generalized Lucas skew circulant type matrices. Appl. Math. Comput. 270, 105–113 (2015)

    MathSciNet  MATH  Google Scholar 

  16. Bozkurt, D., Tam, T.Y.: Determinants and inverses of circulant matrices with Jacobsthal and Jacobsthal-Lucas Numbers. Appl. Math. Comput. 219, 544–551 (2012)

    MathSciNet  MATH  Google Scholar 

  17. Jiang, X.Y., Hong, K.C.: Explicit inverse matrices of Tribonacci skew circulant type matrices. Appl. Math. Comput. 268, 93–102 (2015)

    MathSciNet  MATH  Google Scholar 

  18. Zuo, B.S., Jiang, Z.L., Fu, D.Q.: Determinants and inverses of Ppoeplitz and Ppankel matrices. Spec. Matrices 6, 201–215 (2018)

    Article  MathSciNet  MATH  Google Scholar 

  19. Jiang, Z.L., Wang, W.P., Zheng, Y.P., Zuo, B.S., Niu, B.: Interesting explicit expression of determinants and inverse matrices for Foeplitz and Loeplitz matrices. Mathematics 7(10), 939 (2019)

    Article  Google Scholar 

  20. Jiang, Z.L., Sun, J.X.: Determinant and inverse of a Gaussion Fibonacci skew-Hermitian Toeplitz matrix. J. Nonlinear Sci. Appl. 10, 3694–3707 (2017)

    Article  MathSciNet  MATH  Google Scholar 

  21. Wei, Y.L., Zheng, Y.P., Jiang, Z.L., Shon, S.: The inverses and eigenpairs of tridiagonal Toeplitz matrices with perturbed rows. J. Appl. Math. Comput. (2021). https://doi.org/10.1007/s12190-021-01532-x

    Article  MATH  Google Scholar 

  22. Wei, Y.L., Jiang, X.Y., Jiang, Z.L., Shon, S.: On inverses and eigenpairs of periodic tridiagonal Toeplitz matrices with perturbed corners. J. Appl. Anal. Comput. 10(1), 178–191 (2020)

    MathSciNet  MATH  Google Scholar 

  23. Fu, Y.R., Jiang, X.Y., Jiang, Z.L., Jhang, S.: Properties of a class of perturbed Toeplitz periodic tridiagonal matrices. Comput. Appl. Math. 39, 1–19 (2020)

    Article  MathSciNet  MATH  Google Scholar 

  24. Fu, Y.R., Jiang, X.Y., Jiang, Z.L., Jhang, S.: Inverses and eigenpairs of periodic tridiagonal Toeplitz matrix with opposite-bordered rows. J. Appl. Anal. Comput. 10(4), 1599–1613 (2020)

    MathSciNet  MATH  Google Scholar 

  25. Akbulak, M., Bozkurt, D.: On the norms of Toeplitz matrices involving Fibonacci and Lucas numbers. Hacet. J. Math. Stat. 37(2), 89–95 (2008)

    MathSciNet  MATH  Google Scholar 

  26. Thomas, K.: Fibonacci and Lucas Numbers with Applications. Wiley, Hoboken (2001)

    MATH  Google Scholar 

  27. Zhang, F.Z.: The Schur Complement and Its Applications. Springer, Berlin (2006)

    Google Scholar 

  28. Liu, L., Jiang, Z.L.: Explicit form of the inverse matrices of Tribonacci circulant type matrices. Abstr. Appl. Anal. 2015, 169726 (2015)

    Article  MathSciNet  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding authors

Correspondence to Yanpeng Zheng or Zhaolin Jiang.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

The research was supported by the National Natural Science Foundation of China (No. 12001257 ), the Natural Science Foundation of Shandong Province ( No.ZR2020QA035) and the PhD Research Foundation of Linyi University ( No. LYDX2018BS067)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Meng, Q., Zheng, Y. & Jiang, Z. Determinants and inverses of weighted Loeplitz and weighted Foeplitz matrices and their applications in data encryption. J. Appl. Math. Comput. 68, 3999–4015 (2022). https://doi.org/10.1007/s12190-022-01700-7

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12190-022-01700-7

Keywords

Mathematics Subject Classification