Finite-time synchronization and identification of complex delayed networks with Markovian jumping parameters and stochastic perturbations

2016 ◽  
Vol 86 ◽  
pp. 35-49 ◽  
Author(s):  
Qian Xie ◽  
Gangquan Si ◽  
Yanbin Zhang ◽  
Yiwei Yuan ◽  
Rui Yao
Keyword(s):  
Finite Time ◽  
Time Synchronization ◽  
Markovian Jumping Parameters ◽  
Markovian Jumping ◽  
Stochastic Perturbations

scholarly journals Finite-Time Synchronization of Markovian Jumping Complex Networks with Non-Identical Nodes and Impulsive Effects

Entropy ◽  
2019 ◽  
Vol 21 (8) ◽  
pp. 779
Author(s):  
Tao Chen ◽  
Shiguo Peng ◽  
Zhenhua Zhang
Keyword(s):  
Complex Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Sufficient Conditions ◽  
Impulsive Effects ◽  
Markovian Jumping ◽  
Complex Dynamic Systems ◽  
Synchronization Problem ◽  
Analysis Technique ◽  
Lyapunov Function Method

In this paper, we investigate the finite-time synchronization problem for a class of Markovian jumping complex networks (MJCNs) with non-identical nodes and impulsive effects. Sufficient conditions for the MJCNs are presented based on an M-matrix technique, Lyapunov function method, stochastic analysis technique, and suitable comparison systems to guarantee finite-time synchronization. At last, numerical examples are exploited to illustrate our theoretical results, and they testify the effectiveness of our results for complex dynamic systems.

Robust Finite-Time Passivity for Discrete-Time Genetic Regulatory Networks with Markovian Jumping Parameters

2016 ◽  
Vol 71 (4) ◽  
pp. 289-304 ◽  
Author(s):  
R. Sakthivel ◽  
M. Sathishkumar ◽  
B. Kaviarasan ◽  
S. Marshal Anthoni
Keyword(s):  
Discrete Time ◽  
Finite Time ◽  
Regulatory Networks ◽  
Sufficient Conditions ◽  
Schur Complement ◽  
Genetic Regulatory Networks ◽  
Linear Matrix ◽  
Time Interval ◽  
Markovian Jumping Parameters ◽  
Markovian Jumping

AbstractThis article addresses the issue of robust finite-time passivity for a class of uncertain discrete-time genetic regulatory networks (GRNs) with time-varying delays and Markovian jumping parameters. By constructing a proper Lyapunov–Krasovskii functional involving the lower and upper bounds of time delays, a new set of sufficient conditions is obtained in terms of linear matrix inequalities (LMIs), which guarantees the finite-time boundedness and finite-time passivity of the addressed GRNs for all admissible uncertainties and satisfies the given passive performance index. More precisely, the conditions are obtained with respect to the finite-time interval, while the exogenous disturbances are unknown but energy bounded. Furthermore, the Schur complement together with reciprocally convex optimisation approach is used to simplify the derivation in the main results. Finally, three numerical examples are provided to illustrate the validity of the obtained results.

Finite-time synchronization for memristor-based BAM neural networks with stochastic perturbations and time-varying delays

2018 ◽  
Vol 28 (16) ◽  
pp. 5118-5139 ◽  
Author(s):  
Yanping Zhang ◽  
Lixiang Li ◽  
Haipeng Peng ◽  
Jinghua Xiao ◽  
Yixian Yang ◽  
...  
Keyword(s):  
Neural Networks ◽  
Finite Time ◽  
Time Synchronization ◽  
Time Varying ◽  
Bam Neural Networks ◽  
Stochastic Perturbations
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