Nonlinearly Activated IEZNN Model for Solving Time-Varying Sylvester Equation
Author:
Affiliation:
1. College of Mathematics and Statistics, Jishou University, Jishou, China
2. College of Computer Science and Engineering, Jishou University, Jishou, China
Funder
National Natural Science Foundation of China
Research Foundation of Education Bureau of Hunan Province
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/9668973/09950484.pdf?arnumber=9950484
Reference42 articles.
1. Design and Analysis of New Zeroing Neural Network Models With Improved Finite-Time Convergence for Time-Varying Reciprocal of Complex Matrix
2. Finite-Time Stability and Its Application for Solving Time-Varying Sylvester Equation by Recurrent Neural Network
3. A convergence-accelerated Zhang neural network and its solution application to Lyapunov equation
4. New Pseudoinverse-Based Path-Planning Scheme With PID Characteristic for Redundant Robot Manipulators in the Presence of Noise
5. Improved gradient-based neural networks for online solution of Lyapunov matrix equation
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1. Advances on intelligent algorithms for scientific computing: an overview;Frontiers in Neurorobotics;2023-04-21
2. Dynamic Neural Network Models for Time-Varying Problem Solving: A Survey on Model Structures;IEEE Access;2023
3. Robustness Analysis of a Fixed-Time Convergent GNN for Online Solving Sylvester Equation and Its Application to Robot Path Tracking;IEEE Access;2023
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