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

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, wh...

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Published inAIMS mathematics Vol. 8; no. 11; pp. 27376 - 27395
Main Authors Aoun, Sondess B., Derbel, Nabil, Jerbi, Houssem, Simos, Theodore E., Mourtas, Spyridon D., Katsikis, Vasilios N.
Format Journal Article
LanguageEnglish
Published AIMS Press 01.01.2023
Subjects
chaos control
dynamic sylvester equation
quaternion
zeroing neural network
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Abstract 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.
AbstractList 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.
Author Aoun, Sondess B.
Mourtas, Spyridon D.
Derbel, Nabil
Jerbi, Houssem
Katsikis, Vasilios N.
Simos, Theodore E.
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Snippet 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...
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SubjectTerms chaos control
dynamic sylvester equation
quaternion
zeroing neural network
Title A quaternion Sylvester equation solver through noise-resilient zeroing neural networks with application to control the SFM chaotic system
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