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- Title
Finite-time Convergent Complex-Valued Neural Networks for Computing Square Root of Complex Matrices.
- Authors
Zhaonian Pu; Xuezhong Wang
- Abstract
In this paper, we propose two complex-valued neural networks for finding complex matrix square root by constructing two new types of nonlinear activation functions. Theoretically, we prove that the complex-valued neural networks are globally stable in the sense of Lyapunov stability theory. The state matrix of the complex-valued neural networks converge to the theoretical complex matrix square root in finite time. Numerical simulations are presented to show the effectiveness of the complex-valued neural networks.
- Subjects
SQUARE root; COMPLEX matrices; STABILITY theory; LYAPUNOV stability; NONLINEAR functions
- Publication
IAENG International Journal of Applied Mathematics, 2020, Vol 50, Issue 3, p150
- ISSN
1992-9978
- Publication type
Article