Signum-function array activated ZNN with easier circuit implementation and finite-time convergence for linear systems solving

DOI10.1016/j.ipl.2017.04.008OpenAlexW2606424905MaRDI QIDQ2628272

Yanyan Li

Publication date: 13 June 2017

Published in: Information Processing Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ipl.2017.04.008

zbMATH Keywords

algorithmsreal-time systemsfinite-time convergenceZhang neural network (ZNN)linear systems solvingsignum-function array

Mathematics Subject Classification ID

Numerical linear algebra (65Fxx) Computer aspects of numerical algorithms (65Yxx)

Related Items (3)

Improved Zhang neural network with finite-time convergence for time-varying linear system of equations solving ⋮ Improved zeroing neural models based on two novel activation functions with exponential behavior ⋮ Properties and computation of continuous-time solutions to linear systems

Cites Work

• On one class of iterative methods for obtaining the generalized solution of non-consistent systems of linear algebraic equations
• Time-varying square roots finding via Zhang dynamics versus gradient dynamics and the former's link and new explanation to Newton-Raphson iteration
• Solving linear systems involved in constrained optimization
• Improved gradient-based neural networks for online solution of Lyapunov matrix equation
• Infinitely many Zhang functions resulting in various ZNN models for time-varying matrix inversion with link to Drazin inverse
• Improved neural solution for the Lyapunov matrix equation based on gradient search

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