Brandon Rufino, Ajmal Khan, Tilak Dutta, Elaine Biddiss
Musical instrument classifier for early childhood percussion instruments
PloS one
handling challenge missing measurements nonlinear systems difficult problem various scientific engineering fields missing measurements arise technical faults observation diffusion channel shrinking loss specific metrics bring many challenges estimating state nonlinear systems tackle issue paper proposes technique utilizes robust cubature kalman filter rckf integrating hubers mestimation theory standard conventional cubature kalman filter ckf although ckf often used solving nonlinear filtering problems effectiveness might limited due lack knowledge regarding nonlinear model state noiserelated statistical information contrast rckf demonstrates ability mitigate performance degradation discretization issues related track curves leveraging covariance matrix predictions state estimation output control amidst dynamic disruption errorseven noise statistics deviate prior assumptions performance extended kalman filters ekfs unscented kalman filters ukfs ckfs rckfs compared evaluated using two numerical examples involving univariate nonstationary growth model ungm bearingonly tracking bot numerical experiments demonstrated rckf outperformed ekf enkf ckf effectively handling anomaly errors specifically ungm example rckf achieved significantly lower armse 483 anci 327similar outcomes observed bot example