TY - JOUR
T1 - Quasi-bipartite synchronisation of multiple inertial signed delayed neural networks under distributed event-triggered impulsive control strategy
AU - Udhayakumar, K.
AU - Rihan, Fathalla A.
AU - Li, Xiaodi
AU - Rakkiyappan, R.
N1 - Funding Information:
The authors would like to thank the editor and reviewers for their valuable and constructive comments which improved the quality of this manuscript. This work was funded by the project of fund # 12S005‐UPAR ‐5‐2020, UAE University (UAE).
Publisher Copyright:
© 2021 The Authors. IET Control Theory & Applications published by John Wiley & Sons Ltd on behalf of The Institution of Engineering and Technology
PY - 2021/8
Y1 - 2021/8
N2 - The central concern of this paper is to study leader-following quasi-bipartite synchronisation of a multiple inertial signed neural networks with varying time-delay by utilising distributed event-triggered impulsive control scheme, where connections between adjacent nodes of the neural networks either positive or negative. The second-order neural networks, called inertial neural networks, can be transformed into differential equations of first-order by implementing suitable variable substitution. Under certain hypothesis about the node dynamics, signed graph theory and balanced topology of networks, some conditions are derived in terms of lower-dimensional linear matrix inequalities (LMIs) to achieve leader-following quasi-bipartite synchronisation. In addition, a basic algebraic condition is derived to estimate the theoretical upper bound for the error node. Finally, some numerical simulations are provided to illustrate the correctness of the theoretical results.
AB - The central concern of this paper is to study leader-following quasi-bipartite synchronisation of a multiple inertial signed neural networks with varying time-delay by utilising distributed event-triggered impulsive control scheme, where connections between adjacent nodes of the neural networks either positive or negative. The second-order neural networks, called inertial neural networks, can be transformed into differential equations of first-order by implementing suitable variable substitution. Under certain hypothesis about the node dynamics, signed graph theory and balanced topology of networks, some conditions are derived in terms of lower-dimensional linear matrix inequalities (LMIs) to achieve leader-following quasi-bipartite synchronisation. In addition, a basic algebraic condition is derived to estimate the theoretical upper bound for the error node. Finally, some numerical simulations are provided to illustrate the correctness of the theoretical results.
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U2 - 10.1049/cth2.12146
DO - 10.1049/cth2.12146
M3 - Article
AN - SCOPUS:85104282233
SN - 1751-8644
VL - 15
SP - 1615
EP - 1627
JO - IET Control Theory and Applications
JF - IET Control Theory and Applications
IS - 12
ER -