1. Azam, S.E., Chatzi, E., Papadimitriou, C.: A dual kalman filter approach for state estimation via output-only acceleration measurements. Mech. Syst. Signal Process. 60, 866–886 (2015)
2. Chatzi, E.N., Smyth, A.W.: The unscented kalman filter and particle filter methods for nonlinear structural system identification with non-collocated heterogeneous sensing. Struct. Control Health Monit. Official J. Int. Assoc. Struct. Control, Monit. Eur. Assoc. Control Struct. 16(1), 99–123 (2009)
3. Cuomo, S., Di Cola, V.S., Giampaolo, F., Rozza, G., Raissi, M., Piccialli, F.: Scientific machine learning through physics-informed neural networks: where we are and what’s next. J. Sci. Comput. 92(3), 88 (2022)
4. Dervilis, N., et al.: A nonlinear robust outlier detection approach for SHM. In: Proceedings of 8th International Operational Modal Analysis Conference (IOMAC 2019), pp. 107–114. International Operational Modal Analysis Conference (IOMAC) (2019)
5. Fan, G., Li, J., Hao, H.: Lost data recovery for structural health monitoring based on convolutional neural networks. Struct. Control. Health Monit. 26(10), e2433 (2019)