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. Attached Files Name Description MIMEType Size Downloads Title Discrete-time stochastic quaternion-valued neural networks with time delays: an asymptotic stability analysis Author(s) Sriraman, Ramalingam Rajchakit, Grienggrai 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 Document type: Journal Article Collections: Institute for Intelligent Systems Research and Innovation (IISRI) Open Access Collection GTP Research Related Links Link Description Link to full-text (open access)     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. 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. Versions Version Filter Type Wed, 16 Sep 2020, 14:55:24 EST Thu, 17 Sep 2020, 05:01:57 EST Thu, 17 Sep 2020, 07:31:12 EST Sat, 03 Oct 2020, 06:04:25 EST Tue, 06 Oct 2020, 09:01:43 EST Tue, 06 Oct 2020, 09:03:36 EST Filtered Full Citation counts:   Cited 0 times in TR Web of Science Cited 7 times in Scopus Search Google Scholar Access Statistics: 40 Abstract Views, 0 File Downloads  -  Detailed Statistics Created: Wed, 16 Sep 2020, 14:55:24 EST

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