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

DOI10.1016/j.matcom.2020.06.014OpenAlexW3039860999MaRDI QIDQ1998178

Lin Xiao, Qiuyue Zuo, Qian Yi, Yong-Jun He

Publication date: 6 March 2021

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2020.06.014

zbMATH Keywords

finite-time convergencenonlinear activation functionzeroing neural networktime-varying complex Sylvester equation

Mathematics Subject Classification ID

Numerical linear algebra (65Fxx) Markov processes (60Jxx) Basic linear algebra (15Axx) Probabilistic methods, stochastic differential equations (65Cxx) Computing methodologies and applications (68Uxx)

Related Items (5)

A combined power activation function based convergent factor-variable ZNN model for solving dynamic matrix inversion ⋮ A novel finite-time complex-valued zeoring neural network for solving time-varying complex-valued Sylvester equation ⋮ A noise tolerant parameter-variable zeroing neural network and its applications ⋮ Lopsided DSS iteration method for solving complex Sylvester matrix equation ⋮ Improved finite-time solutions to time-varying Sylvester tensor equation via zeroing neural networks

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