Matches in SemOpenAlex for { <https://semopenalex.org/work/W3035272020> ?p ?o ?g. }
- W3035272020 endingPage "3859" @default.
- W3035272020 startingPage "3849" @default.
- W3035272020 abstract "We derive robust linear filtering and experimental design for systems governed by stochastic differential equations (SDEs) under model uncertainty. Given a model of signal and observation processes, an optimal linear filter is found by solving the Wiener-Hopf equation; with model uncertainty, it is desirable to derive a corresponding robust filter. This article assumes that the physical process is modeled via a SDE system with unknown parameters; the signals are degraded by blurring and additive noise. Due to time-dependent stochasticity in SDE systems, the system is nonstationary; and the resulting Wiener-Hopf equation is difficult to solve in closed form. Hence, we discretize the problem to obtain a matrix system to carry out the overall procedure. We further derive an intrinsically Bayesian robust (IBR) linear filter together with an optimal experimental design framework to determine the importance of SDE parameter(s). We apply the theory to an SDE-based pharmacokinetic two-compartment model to estimate drug concentration levels." @default.
- W3035272020 created "2020-06-19" @default.
- W3035272020 creator A5010097254 @default.
- W3035272020 creator A5013533662 @default.
- W3035272020 creator A5073946580 @default.
- W3035272020 creator A5081620315 @default.
- W3035272020 creator A5082142420 @default.
- W3035272020 date "2020-01-01" @default.
- W3035272020 modified "2023-10-15" @default.
- W3035272020 title "Model-Based Robust Filtering and Experimental Design for Stochastic Differential Equation Systems" @default.
- W3035272020 cites W1510052597 @default.
- W3035272020 cites W1561649271 @default.
- W3035272020 cites W1607843442 @default.
- W3035272020 cites W1666012980 @default.
- W3035272020 cites W1965387924 @default.
- W3035272020 cites W1965986641 @default.
- W3035272020 cites W1972079349 @default.
- W3035272020 cites W1972155227 @default.
- W3035272020 cites W1993136827 @default.
- W3035272020 cites W1995368377 @default.
- W3035272020 cites W2008957577 @default.
- W3035272020 cites W2013562259 @default.
- W3035272020 cites W2049907541 @default.
- W3035272020 cites W2072302356 @default.
- W3035272020 cites W2077761139 @default.
- W3035272020 cites W2078420256 @default.
- W3035272020 cites W2095376999 @default.
- W3035272020 cites W2110266641 @default.
- W3035272020 cites W2113965515 @default.
- W3035272020 cites W2125359511 @default.
- W3035272020 cites W2134717973 @default.
- W3035272020 cites W2135341600 @default.
- W3035272020 cites W2137586026 @default.
- W3035272020 cites W2139251171 @default.
- W3035272020 cites W2156064084 @default.
- W3035272020 cites W2162719021 @default.
- W3035272020 cites W2192916710 @default.
- W3035272020 cites W2287035398 @default.
- W3035272020 cites W2508171925 @default.
- W3035272020 cites W2513723748 @default.
- W3035272020 cites W2582188783 @default.
- W3035272020 cites W2674281613 @default.
- W3035272020 cites W2751779638 @default.
- W3035272020 cites W2835518137 @default.
- W3035272020 cites W2963847210 @default.
- W3035272020 cites W2963885353 @default.
- W3035272020 cites W4211127025 @default.
- W3035272020 cites W44303705 @default.
- W3035272020 doi "https://doi.org/10.1109/tsp.2020.3001384" @default.
- W3035272020 hasPublicationYear "2020" @default.
- W3035272020 type Work @default.
- W3035272020 sameAs 3035272020 @default.
- W3035272020 citedByCount "13" @default.
- W3035272020 countsByYear W30352720202021 @default.
- W3035272020 countsByYear W30352720202022 @default.
- W3035272020 countsByYear W30352720202023 @default.
- W3035272020 crossrefType "journal-article" @default.
- W3035272020 hasAuthorship W3035272020A5010097254 @default.
- W3035272020 hasAuthorship W3035272020A5013533662 @default.
- W3035272020 hasAuthorship W3035272020A5073946580 @default.
- W3035272020 hasAuthorship W3035272020A5081620315 @default.
- W3035272020 hasAuthorship W3035272020A5082142420 @default.
- W3035272020 hasConcept C106131492 @default.
- W3035272020 hasConcept C11413529 @default.
- W3035272020 hasConcept C115961682 @default.
- W3035272020 hasConcept C126255220 @default.
- W3035272020 hasConcept C134306372 @default.
- W3035272020 hasConcept C139722471 @default.
- W3035272020 hasConcept C154945302 @default.
- W3035272020 hasConcept C18537770 @default.
- W3035272020 hasConcept C22597639 @default.
- W3035272020 hasConcept C2775924081 @default.
- W3035272020 hasConcept C28826006 @default.
- W3035272020 hasConcept C31972630 @default.
- W3035272020 hasConcept C33923547 @default.
- W3035272020 hasConcept C41008148 @default.
- W3035272020 hasConcept C41614226 @default.
- W3035272020 hasConcept C47446073 @default.
- W3035272020 hasConcept C51955184 @default.
- W3035272020 hasConcept C6802819 @default.
- W3035272020 hasConcept C73000952 @default.
- W3035272020 hasConcept C78045399 @default.
- W3035272020 hasConcept C99498987 @default.
- W3035272020 hasConceptScore W3035272020C106131492 @default.
- W3035272020 hasConceptScore W3035272020C11413529 @default.
- W3035272020 hasConceptScore W3035272020C115961682 @default.
- W3035272020 hasConceptScore W3035272020C126255220 @default.
- W3035272020 hasConceptScore W3035272020C134306372 @default.
- W3035272020 hasConceptScore W3035272020C139722471 @default.
- W3035272020 hasConceptScore W3035272020C154945302 @default.
- W3035272020 hasConceptScore W3035272020C18537770 @default.
- W3035272020 hasConceptScore W3035272020C22597639 @default.
- W3035272020 hasConceptScore W3035272020C2775924081 @default.
- W3035272020 hasConceptScore W3035272020C28826006 @default.
- W3035272020 hasConceptScore W3035272020C31972630 @default.
- W3035272020 hasConceptScore W3035272020C33923547 @default.
- W3035272020 hasConceptScore W3035272020C41008148 @default.
- W3035272020 hasConceptScore W3035272020C41614226 @default.