Please use this identifier to cite or link to this item:
https://hdl.handle.net/2440/100975
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DC Field | Value | Language |
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dc.contributor.author | Zhang, L. | - |
dc.contributor.author | Zhu, Y. | - |
dc.contributor.author | Shi, P. | - |
dc.contributor.author | Zhao, Y. | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | IEEE Transactions on Cybernetics, 2015; 45(12):2840-2852 | - |
dc.identifier.issn | 2168-2267 | - |
dc.identifier.issn | 2168-2275 | - |
dc.identifier.uri | http://hdl.handle.net/2440/100975 | - |
dc.description.abstract | This paper is concerned with the resilient H∞ filtering problem for a class of discrete-time Markov jump neural networks (NNs) with time-varying delays, unideal measurements, and multiplicative noises. The transitions of NNs modes and desired mode-dependent filters are considered to be asynchronous, and a nonhomogeneous mode transition matrix of filters is used to model the asynchronous jumps to different degrees that are also mode-dependent. The unknown time-varying delays are also supposed to be mode-dependent with lower and upper bounds known a priori. The unideal measurements model includes the phenomena of randomly occurring quantization and missing measurements in a unified form. The desired resilient filters are designed such that the filtering error system is stochastically stable with a guaranteed H∞ performance index. A monotonicity is disclosed in filtering performance index as the degree of asynchronous jumps changes. A numerical example is provided to demonstrate the potential and validity of the theoretical results. | - |
dc.description.statementofresponsibility | Lixian Zhang, Yanzheng Zhu, Peng Shi and Yuxin Zhao | - |
dc.language.iso | en | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.rights | © 2015 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. | - |
dc.source.uri | http://dx.doi.org/10.1109/tcyb.2014.2387203 | - |
dc.subject | time-varying delays; Asynchronous jumps; missing measurements; multiplicative noises; quantization; resilient filter | - |
dc.title | Resilient asynchronous H∞ filtering for Markov jump neural networks with unideal measurements and multiplicative noises | - |
dc.title.alternative | Resilient asynchronous H-infinity filtering for Markov jump neural networks with unideal measurements and multiplicative noises | - |
dc.type | Journal article | - |
dc.identifier.doi | 10.1109/TCYB.2014.2387203 | - |
dc.relation.grant | http://purl.org/au-research/grants/arc/DP140102180 | - |
dc.relation.grant | http://purl.org/au-research/grants/arc/LP140100471 | - |
pubs.publication-status | Published | - |
dc.identifier.orcid | Shi, P. [0000-0001-8218-586X] | - |
Appears in Collections: | Aurora harvest 3 Electrical and Electronic Engineering publications |
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