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Neutral-type of delayed inertial neural networks and their stability analysis using the LMI Approach

Lakshmanan, S., Lim, C.P., Prakash, M., Nahavandi, S. and Balasubramaniam, P. 2017, Neutral-type of delayed inertial neural networks and their stability analysis using the LMI Approach, Neurocomputing, vol. 230, pp. 243-250, doi: 10.1016/j.neucom.2016.12.020.

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Title Neutral-type of delayed inertial neural networks and their stability analysis using the LMI Approach
Author(s) Lakshmanan, S.ORCID iD for Lakshmanan, S. orcid.org/0000-0002-4622-3782
Lim, C.P.ORCID iD for Lim, C.P. orcid.org/0000-0003-4191-9083
Prakash, M.
Nahavandi, S.ORCID iD for Nahavandi, S. orcid.org/0000-0002-0360-5270
Balasubramaniam, P.
Journal name Neurocomputing
Volume number 230
Start page 243
End page 250
Total pages 8
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2017-03-22
ISSN 0925-2312
1872-8286
Keyword(s) Global stability
neural networks
Inertial term
Linear matrix inequality
Neutral delay
Lyapunov–Krasovskii functional
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science
Lyapunov-Krasovskii functional
GLOBAL EXPONENTIAL STABILITY
TIME DELAYS
ROBUST STABILITY
SYSTEMS
Summary A theoretical investigation of neutral-type of delayed inertial neural networks using the Lyapunov stability theory and Linear Matrix Inequality (LMI) approach is presented. Based on a suitable variable transformation, an inertial neural network consisting of second-order differential equations can be converted into a first-order differential model. The sufficient conditions of the delayed inertial neural network are derived by constructing suitable Lyapunov functional candidates, introducing new free weighting matrices, and utilizing the Writinger integral inequality. Through the LMI solution, we analyse the global asymptotic stability condition of the resulting delayed inertial neural network. Simulation examples are presented to demonstrate the effectiveness of the derived analytical results.
Language eng
DOI 10.1016/j.neucom.2016.12.020
Field of Research 099999 Engineering not elsewhere classified
09 Engineering
17 Psychology And Cognitive Sciences
Socio Economic Objective 0 Not Applicable
HERDC Research category C1 Refereed article in a scholarly journal
Copyright notice ©2016, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30093347

Document type: Journal Article
Collection: Centre for Intelligent Systems Research
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