Matches in SemOpenAlex for { <https://semopenalex.org/work/W2968342577> ?p ?o ?g. }
Showing items 1 to 97 of
97
with 100 items per page.
- W2968342577 endingPage "124619" @default.
- W2968342577 startingPage "124619" @default.
- W2968342577 abstract "This work examines the H∞ performance state estimation problem for memory static neural networks (MSNNs) with reliable state feedback stochastic sampled-data control (SSDC). The purpose of presenting this study is to determine whether the H∞ performance and criteria with less conservatism for stability could be gained by SSDC for MSNNs or not. Firstly, we suppose that the sampling interval values follow Bernoulli distribution and the probability of occurrence are teadfast constant, then generalize it to a more universal form. Secondly, on basis of considering the sampling input delay and its sawtooth structure characteristics, a modified augmented Lyapunov-Krasovskii functional (LKF) is constructed on account of the free-matrix-based integral inequality (FMBII) together with generalized free-weighting-matrix (GFWM) inequality, which can reduce the conservatism of H∞ performance criteria. Thirdly, the expected estimator gain matrix can be designed in the light of the solution to linear matrix inequalities (LMIs). Finally, an numerical example is given to check the superiority of the proposed MSNNs control design technique." @default.
- W2968342577 created "2019-08-22" @default.
- W2968342577 creator A5013941056 @default.
- W2968342577 creator A5022392103 @default.
- W2968342577 creator A5034087989 @default.
- W2968342577 creator A5066808082 @default.
- W2968342577 creator A5074368108 @default.
- W2968342577 creator A5085029208 @default.
- W2968342577 date "2020-01-01" @default.
- W2968342577 modified "2023-10-17" @default.
- W2968342577 title "New result on reliable <mml:math xmlns:mml=http://www.w3.org/1998/Math/MathML altimg=si11.svg><mml:msub><mml:mi mathvariant=bold-script>H</mml:mi><mml:mi>∞</mml:mi></mml:msub></mml:math> performance state estimation for memory static neural networks with stochastic sampled-data communication" @default.
- W2968342577 cites W1263167082 @default.
- W2968342577 cites W1963610645 @default.
- W2968342577 cites W1967765281 @default.
- W2968342577 cites W1983512616 @default.
- W2968342577 cites W1985396299 @default.
- W2968342577 cites W1986582332 @default.
- W2968342577 cites W1997686693 @default.
- W2968342577 cites W2018294084 @default.
- W2968342577 cites W2042616129 @default.
- W2968342577 cites W2056717940 @default.
- W2968342577 cites W2066931881 @default.
- W2968342577 cites W2070536907 @default.
- W2968342577 cites W2088612185 @default.
- W2968342577 cites W2096167676 @default.
- W2968342577 cites W2126731256 @default.
- W2968342577 cites W2151970086 @default.
- W2968342577 cites W2157518752 @default.
- W2968342577 cites W2167706556 @default.
- W2968342577 cites W2170272348 @default.
- W2968342577 cites W2511048114 @default.
- W2968342577 cites W2552008386 @default.
- W2968342577 cites W2588591728 @default.
- W2968342577 cites W2603672066 @default.
- W2968342577 cites W2767961957 @default.
- W2968342577 cites W2793790945 @default.
- W2968342577 cites W2803249886 @default.
- W2968342577 cites W2854110366 @default.
- W2968342577 cites W2891433054 @default.
- W2968342577 cites W2903034862 @default.
- W2968342577 cites W2936841212 @default.
- W2968342577 cites W2944599117 @default.
- W2968342577 cites W2954043166 @default.
- W2968342577 cites W2969237641 @default.
- W2968342577 doi "https://doi.org/10.1016/j.amc.2019.124619" @default.
- W2968342577 hasPublicationYear "2020" @default.
- W2968342577 type Work @default.
- W2968342577 sameAs 2968342577 @default.
- W2968342577 citedByCount "5" @default.
- W2968342577 countsByYear W29683425772021 @default.
- W2968342577 countsByYear W29683425772023 @default.
- W2968342577 crossrefType "journal-article" @default.
- W2968342577 hasAuthorship W2968342577A5013941056 @default.
- W2968342577 hasAuthorship W2968342577A5022392103 @default.
- W2968342577 hasAuthorship W2968342577A5034087989 @default.
- W2968342577 hasAuthorship W2968342577A5066808082 @default.
- W2968342577 hasAuthorship W2968342577A5074368108 @default.
- W2968342577 hasAuthorship W2968342577A5085029208 @default.
- W2968342577 hasConcept C105795698 @default.
- W2968342577 hasConcept C106487976 @default.
- W2968342577 hasConcept C11413529 @default.
- W2968342577 hasConcept C159985019 @default.
- W2968342577 hasConcept C185429906 @default.
- W2968342577 hasConcept C192562407 @default.
- W2968342577 hasConcept C28826006 @default.
- W2968342577 hasConcept C33923547 @default.
- W2968342577 hasConceptScore W2968342577C105795698 @default.
- W2968342577 hasConceptScore W2968342577C106487976 @default.
- W2968342577 hasConceptScore W2968342577C11413529 @default.
- W2968342577 hasConceptScore W2968342577C159985019 @default.
- W2968342577 hasConceptScore W2968342577C185429906 @default.
- W2968342577 hasConceptScore W2968342577C192562407 @default.
- W2968342577 hasConceptScore W2968342577C28826006 @default.
- W2968342577 hasConceptScore W2968342577C33923547 @default.
- W2968342577 hasFunder F4320321001 @default.
- W2968342577 hasFunder F4320322768 @default.
- W2968342577 hasFunder F4320327585 @default.
- W2968342577 hasLocation W29683425771 @default.
- W2968342577 hasOpenAccess W2968342577 @default.
- W2968342577 hasPrimaryLocation W29683425771 @default.
- W2968342577 hasRelatedWork W1964781732 @default.
- W2968342577 hasRelatedWork W1968312637 @default.
- W2968342577 hasRelatedWork W1973573083 @default.
- W2968342577 hasRelatedWork W1988224349 @default.
- W2968342577 hasRelatedWork W2014444284 @default.
- W2968342577 hasRelatedWork W2036654869 @default.
- W2968342577 hasRelatedWork W2045590034 @default.
- W2968342577 hasRelatedWork W2084141818 @default.
- W2968342577 hasRelatedWork W2099081348 @default.
- W2968342577 hasRelatedWork W2152704622 @default.
- W2968342577 hasVolume "364" @default.
- W2968342577 isParatext "false" @default.
- W2968342577 isRetracted "false" @default.
- W2968342577 magId "2968342577" @default.
- W2968342577 workType "article" @default.
