@article {math11030600,
	title = {Time-Varying Pseudoinversion Based on Full-Rank Decomposition and Zeroing Neural Networks},
	journal = {Mathematics},
	volume = {11},
	number = {3},
	year = {2023},
	abstract = {The computation of the time-varying matrix pseudoinverse has become crucial in recent years for solving time-varying problems in engineering and science domains. This paper investigates the issue of calculating the time-varying pseudoinverse based on full-rank decomposition (FRD) using the zeroing neural network (ZNN) method, which is currently considered to be a cutting edge method for calculating the time-varying matrix pseudoinverse. As a consequence, for the first time in the literature, a new ZNN model called ZNNFRDP is introduced for time-varying pseudoinversion and it is based on FRD. FourFive numerical experiments investigate and confirm that the ZNNFRDP model performs as well as, if not better than, other well-performing ZNN models in the calculation of the time-varying pseudoinverse. Additionally, theoretical analysis and numerical findings have both supported the effectiveness of the proposed model.},
	issn = {2227-7390},
	doi = {10.3390/math11030600},
	url = {https://www.mdpi.com/2227-7390/11/3/600},
	author = {Alharbi, Hadeel and Jerbi, Houssem and Kchaou, Mourad and Abbassi, Rabeh and Theodore E. Simos and Spyridon D. Mourtas and Vasilios N. Katsikis}
}
