Discrepancy Principle and Stable Parameter Estimation in Avian Influenza
作者： Linda DeCamp
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摘要: In the case of a linear ill-posed problem with noisy data, version an posteriori parameter selection discrepancy principle (DP) [1] is justified for arbitrary regularization strategy under very general assumptions on operator and stabilizer. Its efficiency demonstrated practically important inverse in avian influenza. We refer to our result as abstract (ADP), which shows that applicability DP largely depends level noise data rather than method used construction specific procedure. INDEX WORDS: epidemiology, regularization, principle. DISCREPANCY PRINCIPLE AND STABLE PARAMETER ESTIMATION IN AVIAN INFLUENZA
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