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Discrete-time stochastic quaternion-valued neural networks with time delays: an asymptotic stability analysis

Sriraman, Ramalingam, Rajchakit, Grienggrai, Lim, Chee Peng, Chanthorn, Pharunyou and Samidurai, Rajendran 2020, Discrete-time stochastic quaternion-valued neural networks with time delays: an asymptotic stability analysis, Symmetry, vol. 12, no. 6, pp. 1-26, doi: 10.3390/SYM12060936.

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Title Discrete-time stochastic quaternion-valued neural networks with time delays: an asymptotic stability analysis
Author(s) Sriraman, Ramalingam
Rajchakit, Grienggrai
Lim, Chee PengORCID iD for Lim, Chee Peng orcid.org/0000-0003-4191-9083
Chanthorn, Pharunyou
Samidurai, Rajendran
Journal name Symmetry
Volume number 12
Issue number 6
Article ID 936
Start page 1
End page 26
Total pages 26
Publisher MDPI AG
Place of publication Basel, Switzerland
Publication date 2020-06
ISSN 2073-8994
Keyword(s) stochastic disturbances
quaternion-valued neural networks
real-imaginary separation method
Lyapunov fractional
linear matrix inequality
Summary Stochastic disturbances often cause undesirable characteristics in real-world system modeling. As a result, investigations on stochastic disturbances in neural network (NN) modeling are important. In this study, stochastic disturbances are considered for the formulation of a new class of NN models; i.e., the discrete-time stochastic quaternion-valued neural networks (DSQVNNs). In addition, the mean-square asymptotic stability issue in DSQVNNs is studied. Firstly, we decompose the original DSQVNN model into four real-valued models using the real-imaginary separation method, in order to avoid difficulties caused by non-commutative quaternion multiplication. Secondly, some new sufficient conditions for the mean-square asymptotic stability criterion with respect to the considered DSQVNN model are obtained via the linear matrix inequality (LMI) approach, based on the Lyapunov functional and stochastic analysis. Finally, examples are presented to ascertain the usefulness of the obtained theoretical results.
Language eng
DOI 10.3390/SYM12060936
Indigenous content off
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30142018

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.