2015
DOI: 10.1007/s13369-015-1812-9
|View full text |Cite
|
Sign up to set email alerts
|

Synchronization of Coupled Switched Neural Networks with Time-Varying Delays

Abstract: In this paper, the exponential synchronization problem of delayed coupled switched neural networks with individual node and network topology switching is investigated. By using the matrix decomposing approach and the switched system comparison principle, several synchronization criteria for such complex dynamical networks are obtained. Firstly, under the assumption that all subnetworks are self-synchronized, a sufficient condition is derived in terms of an algebraic inequality. Then, when some subnetworks are … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2

Citation Types

0
2
0

Year Published

2017
2017
2022
2022

Publication Types

Select...
5

Relationship

0
5

Authors

Journals

citations
Cited by 5 publications
(2 citation statements)
references
References 47 publications
(81 reference statements)
0
2
0
Order By: Relevance
“…In [18], each gene expression process can be roughly defined by a continuous dynamic behavior in a gene regulatory network, which is made up of a set of interacting genes, but when the protein concentration exceeds a certain threshold, the regulation kinetics will change abruptly. Furthermore, stable and unstable subsystems usually coexist in complex networks [19][20][21] since some subsystems in a switched system may be unstable due to disturbances, highly nonlinear dynamics, or possible failures [19,22]. As a result, considering switched neural networks (SNNs) with only stable or unstable subsystems are impractical.…”
Section: Introductionmentioning
confidence: 99%
“…In [18], each gene expression process can be roughly defined by a continuous dynamic behavior in a gene regulatory network, which is made up of a set of interacting genes, but when the protein concentration exceeds a certain threshold, the regulation kinetics will change abruptly. Furthermore, stable and unstable subsystems usually coexist in complex networks [19][20][21] since some subsystems in a switched system may be unstable due to disturbances, highly nonlinear dynamics, or possible failures [19,22]. As a result, considering switched neural networks (SNNs) with only stable or unstable subsystems are impractical.…”
Section: Introductionmentioning
confidence: 99%
“…In 2000, in order to analyze the time-varying signal of nonlinear systems, He Xingui proposed 14,15 a spatio-temporal information processing oriented process neural network (PNN). The process neuron structure differs from the traditional neuron in that its input and connection weights can all be timevarying functions, and an time-aggregation is added to the neurons.…”
Section: Introductionmentioning
confidence: 99%