LEADER 01831oam  2200469I  450 
001 9910711922403321
005 20190822093112.0
035   $a(CKB)5470000002488871
035   $a(OCoLC)1089928934
035   $a(OCoLC)995470000002488871
035   $a(EXLCZ)995470000002488871
100   $a20190315j201902    ua             0
101 0 $aeng
135   $aur|||||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 12$aA hybrid framework combining model-based and data-driven methods for hierarchical decentralized robust dynamic state estimation /$fMarcos Netto [and four others]
210  1$aGolden, CO :$cNational Renewable Energy Laboratory,$dFebruary 2019.
215   $a1 online resource (5 pages) $ccolor illustrations
225 1 $aConference paper NREL/CP ;$v5D00-72685
300   $a"February 2019."
300   $a"To be presented at the 2019 IEEE Power and Energy Society General Meeting (IEEE PES GM) Atlanta, Georgia, August 4-8, 2019."
320   $aIncludes bibliographical references (page 5).
606   $aCompressed sensing (Telecommunication)
606   $aKalman filtering
606   $aCompressed sensing (Telecommunication)$2fast
606   $aKalman filtering$2fast
615  0$aCompressed sensing (Telecommunication)
615  0$aKalman filtering.
615  7$aCompressed sensing (Telecommunication)
615  7$aKalman filtering.
700   $aNetto$b Marcos$01401224
712 02$aNational Renewable Energy Laboratory (U.S.),
801  0$bGPO
801  1$bGPO
801  2$bOCLCF
801  2$bGPO
906   $aBOOK
912   $a9910711922403321
996   $aA hybrid framework combining model-based and data-driven methods for hierarchical decentralized robust dynamic state estimation$93474864
997   $aUNINA