简介:Inthispapertheconceptofpositivedefinitebilinearmatrixmomentfunctional.actingonthespaceofallthematrixvaluedcontinuousfunctionsdefinedonaboundedinterval[a,b],isintroduced.ThebestapproximationmatrixproblemwithrespecttosuchafunctionalissolvedintermsofmatrixFourierseries.BasicpropertiesofmatrixFourierseriessuchastheKiemann-Lebesguematrixpropertyandthebessel-parsevalmatrixinequalityareproved.Theconceptoftotalsetvjithrespecttoapositivedefinitematrixfunctionalisintroduced,andthetotallityofanorthonormalsequenceofmatrixpolynomialswithrespecttothefunctional,isestablished.
简介:Inanabstractsetup,wegetstrongtypeinequalitiesinL~(p+1)byassumingweakorextra-weakinequalitiesinOrliczspaces.Forsomeclassesoffunctions,thenumberpisrelatedtoSimonenkoindices.WeapplytheresultstogetstronginequalitiesformaximalfunctionsassociatedtobestΦ-approximationoperatorsinanOrliczspaceL~Φ.
简介:Inthispaper,weconsidertheapproximationproblemofstochasticintegralwithrespecttotwo-parameterWienerprocess.Wefirstintroduceakindofsymmetricintegralandproveitobeysthechainrule.Thenweapplyanintegralformulaofboundedvariationfunctionswithtwovariablestoshowtheapproximationtheoremofstochasticintegralintheplane.Inparticular,weprovethatthesymmetricstochasticintegralisstablewhenthelimitistakeninthesenseofL~2convergence.
简介:Anewmethodologyforprecisegeoiddeterminationwithfinestlocaldetailsbasedonellipsoidalapproximationispresented.Thismethodologyisformulatedthroughthe'fixed-freetwo-boundaryvalueproblem'basedontheobservableofthetypemodulusofgravityintensity,gravityaccelerationandgravitypotentialattheGPSpositionedstations,withsupportoftheknowngeoid'spotentialvalue,W0.
简介:InthispaperweproposetheqanaloguesofmodifiedBaskakov-Sz′aszoperators.Weestimatethemomentsandestablisheddirectresultsintermofmodulusofcontinuity.Anestimatefortherateofconvergenceandweightedapproximationpropertiesoftheqoperatorsarealsoobtained.
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简介:Multidisciplinaryfeasiblemethod(MDF)isconventionalmethodtomultidisciplinaryoptimization(MDO)andwell-understoodbyusers.Itreducesthedimensionsofthemultidisciplinaryoptimizationproblembyusingthedesignvariablesasindependentoptimizationvariables.However,ateachiterationoftheconventionaloptimizationprocedure,multidisciplinaryanalysis(MDA)isnumerouslyperformedthatresultsinextremeexpenseandlowoptimizationefficiency.TheintrinsicweaknessofMDFisduetothetimesthatitloopfixed-pointiterationsinMDA,whichdriveustoimproveMDFbybuildinginexpensiveapproximationsassurrogatesforexpensiveMDA.AnsimpleexampleispresentedtodemonstratetheusefulnessoftheimprovedMDF.ResultsshowthatasignificantreductioninthenumberofmultidisciplinaryanalysisrequiredforoptimizationisobtainedascomparedwithoriginalMDFandtheefficiencyofoptimizationisincreased.
简介:Thispaperanalysesthelocalbehaviorofthesimpleoff-diagonalbivariatequadraticfunctionapproximationtoabivariatefunctionwhichhasagivenpowerseriesexpansionabouttheorigin.Itisshownthatthesimpleoff-diagonalbivariatequadraticHermite-Padéformalwaysdefinesabivariatequadraticfunctionandthatthisfunctionisanalyticinaneighbourhoodoftheorigin.NumericalexamplescomparetheobtainedresultswiththeapproximationpowerofdiagonalChisholmapproximantandTaylorpolynomialapproximant.
简介:ThispaperdevelopsanewlowerboundmethodforPOMDPsthatapproximatestheupdateofabeliefbytheupdateofitsnon-zerostates.ItusestheunderlyingMDPtoexploretheoptimalreachablestatespacefrominitialbeliefandselectactionsduringvalueiterations,whichsignificantlyacceleratestheconvergencespeed.Also,analgorithmwhichcollectsandprunesbeliefpointsbasedontheupperandlowerboundsispresented,andexperimentalresultsshowthatitoutperformssomeofthestate-of-artpoint-basedalgorithms.