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Paper Accepted for Publication in Mechanical Systems and Signal Processing V. Meruane, A. Ortiz-Bernardin, “Structural damage assessment using linear approximation with maximum entropy and transmissibility data.” ABSTRACT Supervised learning algorithms have been proposed as a suitable alternative to model updating methods in structural damage assessment, being Artificial Neural Networks the most frequently used. Notwithstanding, the

V. Meruane, A. Ortiz-Bernardin, “Damage identification using linear approximation with maximum-entropy and transmissibility data,” submitted. ABSTRACT Supervised learning algorithms have been proposed as a suitable alternative to model updating methods in damage assessment, being Artificial Neural Networks the most frequently used. Notwithstanding, the slow learning speed and the large number of parameters that need to