This study illustrates a data driven system identification method for loudspeaker model estimation using the knowledge of the underlying physics of loudspeakers. In this study, diaphragm displacement is analyzed to estimate the model structure and parameters based on impulse response equivalent sampling and autoregressive moving average model. The estimated loudspeaker models are compared in the frequency response function plot. It is shown that the autoregressive moving average (ARMA) based loudspeaker models are comparable to the model estimated by the conventional method based on electrical impedance. Also ARMA modeling strategies with and without knowledge of the physics-based model are compared. Some issues related to ARMA modeling are addressed.
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