简介:Let1
简介:Thegeodesicindifferentialgeometryiseornmonlyusedincomputer-aidedfilamentwinding(CAFW)toavoidslippageinmanufacturingprocess.Theuniquenessofthegeodesicbyitsinitialvaluesseverelyrestrictsthechoiceofthefiberpathandisanobstacletotheproductionofoptimizedstructures.Thispaperpresentsanewclassofmoreflexiblenon-sliptrajectoriesonrevolutionalsurfacesasanextensionofthewell-knownClariautequationandgivesitsapplicationinCAFW.
简介:Inthispaper,byusinganewprojection,weconstructavariantofZhang’salgorithmandproveitsconvergence.Specially,thevariantofZhang’salgorithmhasquadraticterminationandsuperlinearconvergenceraleundercertainconditions.Zhang’salgorithmhasn’ttheseproperties.
简介:Inthispaper,somepropertiesofcentrosymmetricmatrices,whichoftenappearintheconstructionoforthonormalwaveletbasisinwaveletanalysis,areinvestigated.Asanapplication,analgorithmwhichistightlyrelatedtoaso-calledLawtonmatrixispresented.Inthisalgorithm,aboutonlyhalfofmemoryunitsarerequiredandquarterofcomputationalcostisneededbyexploitingthepropertyoftheLawtonmatrixandusingacompressiontechnique,itiscomparedtoonefortheoriginalLawtonmatrix.
简介:Thispaperdiscussespointwiseerrorestimatesfortheapproximationbyboundedlinearoperatorsofcontinuousfunctionsdefinedoncompactmetricspaces(X,d),Theauthorsintroduceanewmajorautofthemodulusofthecontinuitywhichisthesrnallestamongthoseg(ξ)'swhichhavethefollowingpropertiesω(f,ε)≤9(f,ε)andg(f,λε)≤(1+λ)g(f,ε)andbythismajorantanewquantitativeKorovkintypetheoremonanycompactmetricspaceisproved.
简介:Inthispaper,wedefineSumudutransformwithconvergenceconditionsinbicomplexspace.Also,wederivesomeofitsbasicpropertiesanditsinverse.ApplicationsofbicomplexSumudutransformareillustratedtofindthesolutionofdifferentialequationofbicomplex-valuedfunctionsandfindthesolutionforCartesiantransverseelectricmagnetic(TEM)wavesinhomogeneousspace.
简介:Withtheintegral-levelapproachtoglobaloptimization,aclassofdiscon-tinuouspenaltyfunctionsisproposedtosolveconstrainedminimizationproblems.InthispaperweproposeanimplementablealgorithmbymeansofthegoodpointsetofuniformdistributionwhichconquersthedefaultofMonte-Carlomethod.Atlastweprovetheconvergenceoftheimplementablealgorithm.