General Six-Step Discrete-Time Zhang Neural Network for Time-Varying Tensor Absolute Value Equations
This article presents a general six-step discrete-time Zhang neural network (ZNN) for time-varying tensor absolute value equations. Firstly, based on the Taylor expansion theory, we derive a general Zhang et al. discretization (ZeaD) formula, i.e., a general Taylor-type 1-step-ahead numerical differ...
Saved in:
Main Authors: | Min Sun, Jing Liu |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2019-01-01
|
Series: | Discrete Dynamics in Nature and Society |
Online Access: | http://dx.doi.org/10.1155/2019/4861912 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Discrete-Time Zhang Neural Networks for Time-Varying Nonlinear Optimization
by: Min Sun, et al.
Published: (2019-01-01) -
Global Exponential Stability of Discrete-Time Neural Networks with Time-Varying Delays
by: S. Udpin, et al.
Published: (2013-01-01) -
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) -
The modification of the generalized gauss-seidel iteration techniques for absolute value equations
by: Rashid Ali, et al.
Published: (2022-12-01) -
Two-step skeletization of binary images based on the Zhang-Suen model and the producing mask
by: J., Ma, et al.
Published: (2021-04-01)