High-Rate Structural Health Monitoring: Part-III Algorithms
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-34946-1_13
Reference5 articles.
1. Hong, J., Laflamme, S., Dodson, J., Joyce, B.: Introduction to state estimation of high-rate system dynamics. Sensors. 18(1), 217 (2018)
2. Dodson, J., Downey, A., Laflamme, S., Todd, M.D., Moura, A.G., Wang, Y., Mao, Z., Avitabile, P., Blasch, E.: High-rate structural health monitoring and prognostics: an overview. Data Sci. Eng. 9, 213–217 (2022)
3. Hong, J., Laflamme, S., Cao, L., Dodson, J., Joyce, B.: Variable input observer for nonstationary high-rate dynamic systems. Neural Comput. Appl. 32(9), 5015–5026 (2020)
4. Barzegar, V., Laflamme, S., Hu, C., Dodson, J.: Ensemble of recurrent neural networks with LSTM cells for high-rate structural health monitoring. Mech. Syst. Signal Process. 164, 108201 (2022)
5. Nelson, M., Barzegar, V., Laflamme, S., Hu, C., Downey, A.R., Bakos, J.D., Thelen, A., Dodson, J.: Multi-step ahead state estimation with hybrid algorithm for high-rate dynamic systems. Mech. Syst. Signal Process. 182, 109536 (2023)
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