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约束FractionalTikhonov正则化的模迭代方法 Title:IterativeMethodsforConstrainedFractionalTikhonovRegularization Abstract: Regularizationmethodsplayacrucialroleinsolvingill-posedinverseproblemsbymitigatingtheeffectsofnoiseandensuringstablesolutions.OneeffectiveapproachistheTikhonovregularization,whichintroducesaregularizationtermtobalancefidelitytothedataandtheregularizationterm.However,incertaincases,itmaybedesirabletoenforceadditionalconstraintsonthesolution,suchasfractionalorderregularization.ThispaperaimstoexploretheuseofiterativemethodsforconstrainedFractionalTikhonovregularizationinsolvinginverseproblems. 1.Introduction: Inverseproblemsariseinvariousdisciplines,wherethegoalistorecoverunknownparametersorfunctionsfromobserveddata.However,suchproblemsareoftenill-posed,meaningtheylackuniquesolutionsoraresensitivetonoise.Regularizationmethodsaddressthesechallengesbyincorporatingadditionalknowledgeorconstraintsintotheproblemformulation.Tikhonovregularizationisawidelyadoptedapproachthateffectivelybalancesdatafidelityandregularization.ThispaperfocusesonexploringtheextensionofTikhonovregularizationtoincorporatefractionalorderregularizationconstraints. 2.FractionalTikhonovRegularization: FractionalTikhonovregularizationextendstheclassicalTikhonovregularizationbyintroducingafractionalorderregularizationterm.Thefractionalorderregularizationexhibitsmoreflexibilityandadaptabilityincapturingcomplexsignalsandstructures.Theregularizationtermpenalizesthesolutionaccordingtoitsfractionalorderderivative,aidinginregularizingtheinverseproblemsolution.Constraintsonthefractionalordercanbeimposedbasedonpriorknowledgeordesiredpropertiesofthesolution. 3.IterativeMethodsforConstrainedFractionalTikhonovRegularization: IterativemethodsprovideapowerfultoolforsolvingconstrainedfractionalTikhonovregularizationproblems.Thekeyideaistoiterativelyupdatethesolutioninawaythatbalancesdatafidelityandconstraintenforcement.CommoniterativeapproachesincludetheLandweberiteration,theNewtoniteration,andthegradientdescentm