A quaternion Sylvester equation solver through noise-resilient zeroing neural networks with application to control the SFM chaotic system.

Uloženo v:
Podrobná bibliografie
Název: A quaternion Sylvester equation solver through noise-resilient zeroing neural networks with application to control the SFM chaotic system.
Autoři: Aoun, Sondess B., Derbel, Nabil, Jerbi, Houssem, Simos, Theodore E., Mourtas, Spyridon D., Katsikis, Vasilios N.
Zdroj: AIMS Mathematics; 2023, Vol. 8 Issue 11, p27376-27395, 20p
Témata: SYLVESTER matrix equations, QUATERNIONS, SINE function, PROBLEM solving
Abstrakt: Dynamic Sylvester equation (DSE) problems have drawn a lot of interest from academics due to its importance in science and engineering. Due to this, the quest for the quaternion DSE (QDSE) solution is the subject of this work. This is accomplished using the zeroing neural network (ZNN) technique, which has achieved considerable success in tackling time-varying issues. Keeping in mind that the original ZNN can handle QDSE successfully in a noise-free environment, but it might not work in a noisy one, and the noise-resilient ZNN (NZNN) technique is also utilized. In light of that, one new ZNN model is introduced to solve the QDSE problem and one new NZNN model is introduced to solve the QDSE problem under different types of noises. Two simulation experiments and one application to control of the sine function memristor (SFM) chaotic system show that the models function superbly. [ABSTRACT FROM AUTHOR]
Copyright of AIMS Mathematics is the property of American Institute of Mathematical Sciences and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáze: Complementary Index
Popis
Abstrakt:Dynamic Sylvester equation (DSE) problems have drawn a lot of interest from academics due to its importance in science and engineering. Due to this, the quest for the quaternion DSE (QDSE) solution is the subject of this work. This is accomplished using the zeroing neural network (ZNN) technique, which has achieved considerable success in tackling time-varying issues. Keeping in mind that the original ZNN can handle QDSE successfully in a noise-free environment, but it might not work in a noisy one, and the noise-resilient ZNN (NZNN) technique is also utilized. In light of that, one new ZNN model is introduced to solve the QDSE problem and one new NZNN model is introduced to solve the QDSE problem under different types of noises. Two simulation experiments and one application to control of the sine function memristor (SFM) chaotic system show that the models function superbly. [ABSTRACT FROM AUTHOR]
ISSN:24736988
DOI:10.3934/math.20231401