Improved finite-time zeroing neural networks for time-varying complex Sylvester equation solving

Lin Xiao, Qian Yi, Qiuyue Zuo and Yongjun He

Mathematics and Computers in Simulation (MATCOM), 2020, vol. 178, issue C, 246-258

Abstract: There are two equivalent methods for dealing with the nonlinearity of complex-valued problems. The first method is to handle the real part and imaginary part of complex inputs, and the second method is to handle the modulus of complex inputs. Based on these two methods, this paper explores a superior nonlinear activation function and proposes two improved finite-time zeroing neural network (IFTZNN) models for time-varying complex Sylvester equation solving. Regarding the existing neural model activated by the sign-bi-power (SBP) activation function, the convergence upper bounds of the IFTZNN models are much smaller, and thus we can estimate their convergence time more accurately. Furthermore, the detailed theoretical analysis of the IFTZNN models is provided to show their effectiveness. Comparative simulation results also verify the advantages of our proposed IFTZNN models for complex Sylvester equation solving.

Keywords: Zeroing neural network; Finite-time convergence; Time-varying complex Sylvester equation; Nonlinear activation function (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378475420302160
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:178:y:2020:i:c:p:246-258

DOI: 10.1016/j.matcom.2020.06.014

Access Statistics for this article

Mathematics and Computers in Simulation (MATCOM) is currently edited by Robert Beauwens

More articles in Mathematics and Computers in Simulation (MATCOM) from Elsevier
Bibliographic data for series maintained by Catherine Liu ().