Stochastically exponential synchronization for Markov jump neural networks with time-varying delays via event-triggered control scheme
Abstract This paper focuses on the stochastically exponential synchronization problem for one class of neural networks with time-varying delays (TDs) and Markov jump parameters (MJPs). To derive a tighter bound of reciprocally convex quadratic terms, we provide an improved reciprocally convex combin...
Main Authors: | Xiaoman Liu, Haiyang Zhang, Jun Yang, Hao Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
SpringerOpen
2021-01-01
|
Series: | Advances in Difference Equations |
Subjects: | |
Online Access: | https://doi.org/10.1186/s13662-020-03109-7 |
Similar Items
-
Event-triggered H∞ filtering for discrete-time Markov jump delayed neural networks with quantizations
by: Tingting Zhang, et al.
Published: (2018-09-01) -
Exponential Stability of Markovian Jumping Memristor-Based Neural Networks via Event-Triggered Impulsive Control Scheme
by: Nijing Yang, et al.
Published: (2020-01-01) -
New results of exponential synchronization of complex network with time-varying delays
by: Yiping Luo, et al.
Published: (2019-01-01) -
Exponential Synchronization of Switched Neural Networks With Mixed Time-Varying Delays via Static/Dynamic Event-Triggering Rules
by: Yuting Cao, et al.
Published: (2020-01-01) -
Fixed-time synchronization of semi-Markovian jumping neural networks with time-varying delays
by: Wei Zhao, et al.
Published: (2018-06-01)