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DC Field | Value | Language |
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dc.contributor.author | Liu, Y | - |
dc.contributor.author | Wang, Z | - |
dc.contributor.author | Liu, X | - |
dc.date.accessioned | 2012-09-21T08:46:31Z | - |
dc.date.available | 2012-09-21T08:46:31Z | - |
dc.date.issued | 2012 | - |
dc.identifier.citation | Neural Processing Letters, 36(1): 1 - 19, Aug 2012 | en_US |
dc.identifier.issn | 1370-4621 | - |
dc.identifier.uri | http://link.springer.com/article/10.1007/s11063-012-9219-z?null | en |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/6692 | - |
dc.description | Copyright @ 2012 Springer Verlag | en_US |
dc.description.abstract | This paper is concerned with the state estimation problem for a new class of discrete-time neural networks with Markovian jumping parameters and mixed time-delays. The parameters of the neural networks under consideration switch over time subject to a Markov chain. The networks involve both the discrete-time-varying delay and the mode-dependent distributed time-delay characterized by the upper and lower boundaries dependent on the Markov chain. By constructing novel Lyapunov-Krasovskii functionals, sufficient conditions are firstly established to guarantee the exponential stability in mean square for the addressed discrete-time neural networks with Markovian jumping parameters and mixed time-delays. Then, the state estimation problem is coped with for the same neural network where the goal is to design a desired state estimator such that the estimation error approaches zero exponentially in mean square. The derived conditions for both the stability and the existence of desired estimators are expressed in the form of matrix inequalities that can be solved by the semi-definite programme method. A numerical simulation example is exploited to demonstrate the usefulness of the main results obtained. | en_US |
dc.description.sponsorship | This work was supported in part by the Royal Society of the U.K., the National Natural Science Foundation of China under Grants 60774073 and 61074129, and the Natural Science Foundation of Jiangsu Province of China under Grant BK2010313. | en_US |
dc.language.iso | en | en_US |
dc.publisher | Springer Verlag | en_US |
dc.subject | Discrete-time neural networks | en_US |
dc.subject | Mixed time-delays | en_US |
dc.subject | Markovian jumping parameters | en_US |
dc.subject | Exponential stability | en_US |
dc.subject | State estimate | en_US |
dc.subject | Linear matrix inequality | en_US |
dc.title | State estimation for discrete-time neural networks with Markov-mode-dependent lower and upper bounds on the distributed delays | en_US |
dc.type | Article | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/s11063-012-9219-z | - |
pubs.organisational-data | /Brunel | - |
pubs.organisational-data | /Brunel/Brunel Active Staff | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths | - |
pubs.organisational-data | /Brunel/Brunel Active Staff/School of Info. Systems, Comp & Maths/IS and Computing | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Health Sciences and Social Care - URCs and Groups/Centre for Systems and Synthetic Biology | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups | - |
pubs.organisational-data | /Brunel/University Research Centres and Groups/School of Information Systems, Computing and Mathematics - URCs and Groups/Centre for Information and Knowledge Management | - |
Appears in Collections: | Publications Computer Science Dept of Computer Science Research Papers |
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