2008
DOI: 10.1109/tac.2008.929368
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Generalized Lyapunov Equation Approach to State-Dependent Stochastic Stabilization/Detectability Criterion

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Cited by 167 publications
(146 citation statements)
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“…Zhang and Chen [16] introduced the exact observability for stochastic Itô systems, while the exact detectability was, respectively, defined in [14] and [17]. In [6], the authors gave the notions of W-observability and W-detectability for Markov jump linear systems without multiplicative noise, where several equivalent conditions were derived.…”
Section: Exact Observability and Exact Detectabilitymentioning
confidence: 99%
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“…Zhang and Chen [16] introduced the exact observability for stochastic Itô systems, while the exact detectability was, respectively, defined in [14] and [17]. In [6], the authors gave the notions of W-observability and W-detectability for Markov jump linear systems without multiplicative noise, where several equivalent conditions were derived.…”
Section: Exact Observability and Exact Detectabilitymentioning
confidence: 99%
“…In recent years, these concepts have been extended to stochastic linear systems [6,9,14,16−17] . In [14,[16][17], the authors introduced the exact observability and detectability of stochastic Itô-systems without jump parameters. Costa and Vol [6] dealt with similar topic to that of the present paper for the jump linear system without multiplicative noises.…”
Section: Introductionmentioning
confidence: 99%
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“…Stochastic noise is ubiquitous [14][15][16] and stochastic delay differential systems (SDDSs) have been one of the focuses of scientific research for many years. Many properties of SDDSs have been studied and lots of papers were published; see [17,18] and the references therein.…”
Section: Introductionmentioning
confidence: 99%
“…These important concepts of stochastic Itô systems have attracted much attention [6][7][8][9]13]. Recently, stochastic stability and stabilization by using the method of generalized Lyapunov equation (GLE) was presented in [8], which extended the deterministic theory to stochastic cases.…”
Section: Introductionmentioning
confidence: 99%