Article

Li, S., Zhang, A-M., Han, R. and Ma, Q. ORCID: 0000-0001-5579-6454 (2019). 3D full coupling model for strong interaction between a pulsating bubble and a movable sphere. Journal of Computational Physics, 392, pp. 713-731. doi: 10.1016/j.jcp.2019.05.001

Li, S., Won, H., Fu, X., Fairbank, M., Wunsch, D. C. and Alonso, E. ORCID: 0000-0002-3306-695X (2019). Neural-Network Vector Controller for Permanent-Magnet Synchronous Motor Drives: Simulated and Hardware-Validated Results. IEEE Transactions on Cybernetics, doi: 10.1109/TCYB.2019.2897653

Fu, X., Li, S., Fairbank, M., Wunsch, D. C. and Alonso, E. (2015). Training Recurrent Neural Networks With the Levenberg-Marquardt Algorithm for Optimal Control of a Grid-Connected Converter. IEEE Transactions on Neural Networks and Learning Systems, 26(9), pp. 1900-1912. doi: 10.1109/TNNLS.2014.2361267

Xu, Q., Gong, P., Chen, T., Michael, J. and Li, S. (2015). Modelling and characterization of NAND flash memory channels. Measurement, 70, pp. 225-231. doi: 10.1016/j.measurement.2015.04.003

Li, S., Oikonomou, G., Tryfonas, T., Chen, T. and Xu, L. D. (2014). A Distributed Consensus Algorithm for Decision Making in Service-Oriented Internet of Things. IEEE Transactions on Industrial Informatics, 10(2), pp. 1461-1468. doi: 10.1109/TII.2014.2306331

Fairbank, M., Li, S., Fu, X., Alonso, E. and Wunsch, D. C. (2014). An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances. Neural Networks, 49, pp. 74-86. doi: 10.1016/j.neunet.2013.09.010

Li, S., Fairbank, M., Johnson, C., Wunsch, D. C., Alonso, E. and Proano, J. L. (2013). Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions. IEEE Transactions on Neural Networks and Learning Systems, 25(4), pp. 738-750. doi: 10.1109/TNNLS.2013.2280906

Book Section

Al-Arif, S. M., Gundry, M., Knapp, K. and Slabaugh, G. G. (2017). Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Vertebrae. In: Yao, J., Vrtovec, T., Zheng, G., Frangi, A., Glocker, B. and Li, S. (Eds.), Improving an Active Shape Model with Random Classification Forest for Segmentation of Cervical Vertebrae. Lecture Notes in Computer Science, 10182. (pp. 3-15). Cham: Springer. ISBN 978-3-319-55049-7

Li, S., Fairbank, M., Fu, X., Wunsch, D. C. and Alonso, E. (2013). Nested-Loop Neural Network Vector Control of Permanent Magnet Synchronous Motors. In: India Conference, 2008. INDICON 2008. Annual IEEE. (pp. 81-86). IEEE. ISBN 978-1-4673-6128-6

Conference or Workshop Item

Chen, C., Ouyang, C., Tarroni, G. ORCID: 0000-0002-0341-6138, Schlemper, J., Qiu, H., Bai, W. and Rueckert, D. (2020). Unsupervised Multi-modal Style Transfer for Cardiac MR Segmentation. In: Pop, M., Sermesant, M., Camara, O., Zhuang, X., Li, S., Young, A., Mansi, T. and Suinesiaputra, A. (Eds.), Statistical Atlases and Computational Models of the Heart. Multi-Sequence CMR Segmentation, CRT-EPiggy and LV Full Quantification Challenges. STACOM 2019. (pp. 209-219). Cham, Switzerland: Springer. ISBN 978-3-030-39073-0

Li, S., Fu, X., Alonso, E., Fairbank, M. and Wunsch, D. C. (2016). Neural-network based vector control of VSCHVDC transmission systems. Paper presented at the 4th International Conference on Renewable Energy Research and Applications (ICRERA), 22-25 Nov 2015, Palermo, Italy.

Li, S., Alonso, E., Fairbank, M., Jaithwa, I. and Wunsch, D. C. (2015). Hardware Validation for Control of Three-Phase Grid-Connected Microgrids Using Artificial Neural Networks. Paper presented at the 12th International Conference on Applied Computing 2015, 24-10-2015 - 26-10-2015, Maynooth, Ireland.

Li, S., Fairbank, M., Wunsch, D. C. and Alonso, E. (2012). Vector Control of a Grid-Connected Rectifier/Inverter Using an Artificial Neural Network. Paper presented at the IEEE International Joint Conference on Neural Networks (IEEE IJCNN 2012), 1783-1789, 10-15-2012, Brisbane, Australia.