A novel predefined-time noise-tolerant zeroing neural network for solving time-varying generalized linear matrix equations

DOI10.1016/j.jfranklin.2023.09.009OpenAlexW4386790636MaRDI QIDQ6082822

Publication date: 30 October 2023

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2023.09.009

Mathematics Subject Classification ID

Iterative numerical methods for linear systems (65F10) Direct numerical methods for linear systems and matrix inversion (65F05)

Cites Work

Novel data filtering based parameter identification for multiple-input multiple-output systems using the auxiliary model
Gradient based and least squares based iterative algorithms for matrix equations \(AXB + CX^{T}D = F\)
Extended Arnoldi methods for large low-rank Sylvester matrix equations
Zhang neural network for online solution of time-varying convex quadratic program subject to time-varying linear-equality constraints
Krylov-subspace methods for the Sylvester equation
Finite iterative solutions to periodic Sylvester matrix equations
Direct methods for matrix Sylvester and Lyapunov equations
Reduced-rank gradient-based algorithms for generalized coupled Sylvester matrix equations and its applications
Conjugate gradient-based iterative algorithm for solving generalized periodic coupled Sylvester matrix equations
Factor gradient iterative algorithm for solving a class of discrete periodic Sylvester matrix equations
A combined power activation function based convergent factor-variable ZNN model for solving dynamic matrix inversion
A new noise-tolerant and predefined-time ZNN model for time-dependent matrix inversion
Quasi gradient-based inversion-free iterative algorithm for solving a class of the nonlinear matrix equations
Partially-coupled nonlinear parameter optimization algorithm for a class of multivariate hybrid models
Weighted and deflated global GMRES algorithms for solving large Sylvester matrix equations
A note on the numerical approximate solutions for generalized Sylvester matrix equations with applications
Iterative solutions of the generalized Sylvester matrix equations by using the hierarchical identification principle
Iterative least-squares solutions of coupled sylvester matrix equations
A finite-time convergent dynamic system for solving online simultaneous linear equations
On Iterative Solutions of General Coupled Matrix Equations
Performance Analysis of Gradient Neural Network Exploited for Online Time-Varying Matrix Inversion
Refinements of the Hadamard and Cauchy-Schwarz inequalities with two inequalities of the principal angles
Nonlinear Feedback Design for Fixed-Time Stabilization of Linear Control Systems
Separable multi-innovation Newton iterative modeling algorithm for multi-frequency signals based on the sliding measurement window
Least squares parameter estimation and multi-innovation least squares methods for linear fitting problems from noisy data
Separable synthesis gradient estimation methods and convergence analysis for multivariable systems

This page was built for publication: A novel predefined-time noise-tolerant zeroing neural network for solving time-varying generalized linear matrix equations