AIMS Mathematics (Apr 2023)

Zeroing neural networks for computing quaternion linear matrix equation with application to color restoration of images

  • Vladislav N. Kovalnogov ,
  • Ruslan V. Fedorov,
  • Denis A. Demidov,
  • Malyoshina A. Malyoshina,
  • Theodore E. Simos,
  • Vasilios N. Katsikis ,
  • Spyridon D. Mourtas,
  • Romanos D. Sahas

DOI
https://doi.org/10.3934/math.2023733
Journal volume & issue
Vol. 8, no. 6
pp. 14321 – 14339

Abstract

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The importance of quaternions in a variety of fields, such as physics, engineering and computer science, renders the effective solution of the time-varying quaternion matrix linear equation (TV-QLME) an equally important and interesting task. Zeroing neural networks (ZNN) have seen great success in solving TV problems in the real and complex domains, while quaternions and matrices of quaternions may be readily represented as either a complex or a real matrix, of magnified size. On that account, three new ZNN models are developed and the TV-QLME is solved directly in the quaternion domain as well as indirectly in the complex and real domains for matrices of arbitrary dimension. The models perform admirably in four simulation experiments and two practical applications concerning color restoration of images.

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