TY - JOUR
T1 - Synchronization in Quaternion-Valued Neural Networks with Delay and Stochastic Impulses
AU - Li, Chengsheng
AU - Cao, Jinde
AU - Kashkynbayev, Ardak
N1 - Funding Information:
AK was funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan Grant “Dynamical Analysis and Synchronization of Complex Neural Networks with Its Applications”.
Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/2
Y1 - 2022/2
N2 - A class of global exponential synchronization problem for delayed quaternion-valued neural networks with stochastic impulses has been investigated in this paper, where the impulses arouse time and strength both are randomly. Firstly, the delayed quaternion-valued model with stochastic impulses was fain to separate to four real-valued parts in consideration of the fact that noncommutativity character of quaternion multiplication. Then, a new criterion was obtained to achieve the global exponential synchronization via building an appropriate classically Lyapunov candidate function and utilizing the method of comparison principle and reduction to absurdity. Finally, in order to verify the validity of the proposed theorem, a given numerical example is provided.
AB - A class of global exponential synchronization problem for delayed quaternion-valued neural networks with stochastic impulses has been investigated in this paper, where the impulses arouse time and strength both are randomly. Firstly, the delayed quaternion-valued model with stochastic impulses was fain to separate to four real-valued parts in consideration of the fact that noncommutativity character of quaternion multiplication. Then, a new criterion was obtained to achieve the global exponential synchronization via building an appropriate classically Lyapunov candidate function and utilizing the method of comparison principle and reduction to absurdity. Finally, in order to verify the validity of the proposed theorem, a given numerical example is provided.
KW - Delayed quaternion-valued neural network
KW - Global exponential synchronization
KW - Stochastic impulses
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U2 - 10.1007/s11063-021-10653-0
DO - 10.1007/s11063-021-10653-0
M3 - Article
AN - SCOPUS:85117220498
SN - 1370-4621
VL - 54
SP - 691
EP - 708
JO - Neural Processing Letters
JF - Neural Processing Letters
IS - 1
ER -