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Mansoori, A., Eshaghnezhad, M. and Effati, S. (2018) An Efficient Neural Network Model for Solving the Absolute Value Equations. IEEE Transactions on Circuits and Systems II: Express Briefs, 65, 391-395.
https://doi.org/10.1109/tcsii.2017.2750065

has been cited by the following article:

• TITLE: A Novel Inverse-Free Neurodynamic Approach for Solving Absolute Value Equations

  AUTHORS: Tao Li

  KEYWORDS: Absolute Value Equations, Neurodynamic Approach, Fixed-Time Convergence, Numerical Simulations

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.12 No.10, October 28, 2024

  ABSTRACT: We propose a novel inverse-free neurodynamic approach (NIFNA) for solving absolute value equations (AVE). The NIFNA guarantees global convergence and notably improves convergence speed by achieving fixed-time convergence. To validate the theoretical findings, numerical simulations are conducted, demonstrating the effectiveness and efficiency of the proposed NIFNA.