A New Varying-Factor Finite-Time Recurrent Neural Network to Solve the Time-Varying Sylvester Equation Online
This paper presents a varying-parameter finite-time recurrent neural network, called a varying-factor finite-time recurrent neural network (VFFTRNN), which is able to solve the solution of the time-varying Sylvester equation online. The proposed neural network makes the matrix coefficients vary with...
Saved in:
| Main Authors: | Haoming Tan, Junyun Wu, Hongjie Guan, Zhijun Zhang, Ling Tao, Qingmin Zhao, Chunquan Li |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
|
| Series: | Mathematics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7390/12/24/3891 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Novel Prescribed-Time Convergence Acceleration Algorithm with Time Rescaling
by: Xuehui Mei, et al.
Published: (2025-01-01) -
Relations between exponential laws for spaces of C∞-functions
by: Peter Biström
Published: (1997-01-01) -
Parameter uniform finite difference formulation with oscillation free for solving singularly perturbed delay parabolic differential equation via exponential spline
by: Zerihun Ibrahim Hassen, et al.
Published: (2025-01-01) -
Stability of Stochastic Coupled Networks with Time-Varying Coupling Under Intermittent Event-Triggered Control
by: Yongbao Wu, et al.
Published: (2024-11-01) -
Global exponential synchronization of discrete-time high-order BAM neural networks with multiple time-varying delays
by: Er-yong Cong, et al.
Published: (2024-11-01)