Finite-/fixed-time anti-synchronization of neural networks with leakage delays under discontinuous disturbances

2022 ◽  
Vol 155 ◽  
pp. 111639
Author(s):  
Lian Duan ◽  
Jinzhi Liu ◽  
Chuangxia Huang ◽  
Zengyun Wang
Keyword(s):  
Neural Networks ◽  
Fixed Time ◽  
Leakage Delays

Quasi fixed-time synchronization of memristive Cohen-Grossberg neural networks with reaction-diffusion

2020 ◽  
Vol 415 ◽  
pp. 74-83
Author(s):  
Fangmin Ren ◽  
Minghui Jiang ◽  
Hao Xu ◽  
Mengqin Li
Keyword(s):  
Neural Networks ◽  
Time Synchronization ◽  
Reaction Diffusion ◽  
Fixed Time

The multi-constrained least-cost multicast problem with neural networks in fixed time

2016 ◽  
Vol 10 ◽  
pp. 931-945
Author(s):  
N. Saber ◽  
M. Mestari ◽  
A. Ait El Mahjoub
Keyword(s):  
Neural Networks ◽  
Fixed Time

scholarly journals Passivity of Memristive BAM Neural Networks with Probabilistic and Mixed Time-Varying Delays

2018 ◽  
Vol 2018 ◽  
pp. 1-25
Author(s):  
Weiping Wang ◽  
Meiqi Wang ◽  
Xiong Luo ◽  
Lixiang Li ◽  
Wenbing Zhao
Keyword(s):  
Neural Networks ◽  
Probability Distribution ◽  
Linear Matrix ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Bernoulli Distribution ◽  
Matrix Inequalities ◽  
Bidirectional Associative Memory ◽  
Leakage Delays ◽  
Numerical Examples

This paper is concerned with the passivity problem of memristive bidirectional associative memory neural networks (MBAMNNs) with probabilistic and mixed time-varying delays. By applying random variables with Bernoulli distribution, the information of probability time-varying delays is taken into account. Furthermore, we consider the probability distribution of the variation and the extent of the delays; therefore, the results derived are less conservative than in the existing papers. In particular, the leakage delays as well as distributed delays are all taken into consideration. Based on appropriate Lyapunov-Krasovskii functionals (LKFs) and some useful inequalities, several conditions for passive performance are established in linear matrix inequalities (LMIs). Finally, numerical examples are given to demonstrate the feasibility of the presented theories, and the results reveal that the probabilistic and mixed time-varying delays have an unstable influence on the system and should not be ignored.

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