@article {math10244759,
	title = {Computation of Time-Varying {2,3}- and {2,4}-Inverses through Zeroing Neural Networks},
	journal = {Mathematics},
	volume = {10},
	number = {24},
	year = {2022},
	abstract = {This paper investigates the problem of computing the time-varying {2,3}- and {2,4}-inverses through the zeroing neural network (ZNN) method, which is presently regarded as a state-of-the-art method for computing the time-varying matrix Moore\&ndash;Penrose inverse. As a result, two new ZNN models, dubbed ZNN23I and ZNN24I, for the computation of the time-varying {2,3}- and {2,4}-inverses, respectively, are introduced, and the effectiveness of these models is evaluated. Numerical experiments investigate and confirm the efficiency of the proposed ZNN models for computing the time-varying {2,3}- and {2,4}-inverses.},
	issn = {2227-7390},
	doi = {10.3390/math10244759},
	url = {https://www.mdpi.com/2227-7390/10/24/4759},
	author = {Li, Xingyuan and Lin, Chia-Liang and Theodore E. Simos and Spyridon D. Mourtas and Vasilios N. Katsikis}
}
