Publication: Finite-Time Passivity-Based Stability Criteria for Delayed Discrete-Time Neural Networks via New Weighted Summation Inequalities
| dc.contributor.author | Ramasamy Saravanakumar | en_US |
| dc.contributor.author | Sreten B. Stojanovic | en_US |
| dc.contributor.author | Damnjan D. Radosavljevic | en_US |
| dc.contributor.author | Choon Ki Ahn | en_US |
| dc.contributor.author | Hamid Reza Karimi | en_US |
| dc.contributor.other | University of Niš | en_US |
| dc.contributor.other | Universiteti i Prishtines | en_US |
| dc.contributor.other | Politecnico di Milano | en_US |
| dc.contributor.other | Mahidol University | en_US |
| dc.contributor.other | Kunsan National University | en_US |
| dc.contributor.other | Korea University | en_US |
| dc.date.accessioned | 2020-01-27T08:24:27Z | |
| dc.date.available | 2020-01-27T08:24:27Z | |
| dc.date.issued | 2019-01-01 | en_US |
| dc.description.abstract | © 2012 IEEE. In this paper, we study the problem of finite-time stability and passivity criteria for discrete-time neural networks (DNNs) with variable delays. The main objective is how to effectively evaluate the finite-time passivity conditions for NNs. To achieve this, some new weighted summation inequalities are proposed for application to a finite-sum term appearing in the forward difference of a novel Lyapunov-Krasovskii functional, which helps to ensure that the considered delayed DNN is passive. The derived passivity criteria are presented in terms of linear matrix inequalities. A numerical example is given to illustrate the effectiveness of the proposed results. | en_US |
| dc.identifier.citation | IEEE Transactions on Neural Networks and Learning Systems. Vol.30, No.1 (2019), 58-71 | en_US |
| dc.identifier.doi | 10.1109/TNNLS.2018.2829149 | en_US |
| dc.identifier.issn | 21622388 | en_US |
| dc.identifier.issn | 2162237X | en_US |
| dc.identifier.other | 2-s2.0-85047638906 | en_US |
| dc.identifier.uri | https://repository.li.mahidol.ac.th/handle/20.500.14594/50695 | |
| dc.rights | Mahidol University | en_US |
| dc.rights.holder | SCOPUS | en_US |
| dc.source.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85047638906&origin=inward | en_US |
| dc.subject | Computer Science | en_US |
| dc.title | Finite-Time Passivity-Based Stability Criteria for Delayed Discrete-Time Neural Networks via New Weighted Summation Inequalities | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication | |
| mu.datasource.scopus | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85047638906&origin=inward | en_US |