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A linear model of lung mechanics is analyzed in the following report. The model corresponds to an RLC circuit with unknown parameters. Parametric identification allows to trace the system governance coefficients once a mathematical model has been estimated. Different approaches allow to minimize the difference between the estimated parameters and the real measures. An approach without numerical differentiation is addressed, using the Nelder-Mead algorithm and an approach using the relaxed Gauss-Newton method. Both methods lead to the correct estimation of the parameters but some considerations allow to optimize their performance.

Home Page: https://alessandromastrofini.it/en/identification-rlc-respiratory/