| A review of feature extraction and performance evaluation in epileptic seizure detection using EEG P Boonyakitanont, A Lek-Uthai, K Chomtho, J Songsiri Biomedical Signal Processing and Control 57, 101702, 2020 | 184 | 2020 |
| Critical comments on EEG sensor space dynamical connectivity analysis F Van de Steen, L Faes, E Karahan, J Songsiri, PA Valdes-Sosa, ... Brain topography 32, 643-654, 2019 | 149 | 2019 |
| Topology selection in graphical models of autoregressive processes J Songsiri, L Vandenberghe The Journal of Machine Learning Research 11, 2671-2705, 2010 | 104 | 2010 |
| Graphical models of autoregressive processes. J Songsiri, J Dahl, L Vandenberghe Convex optimization in signal processing and communications, 89-116, 2010 | 70 | 2010 |
| CU-BEMS, smart building electricity consumption and indoor environmental sensor datasets M Pipattanasomporn, G Chitalia, J Songsiri, C Aswakul, W Pora, ... Scientific Data 7 (1), 241, 2020 | 54 | 2020 |
| Sparse autoregressive model estimation for learning Granger causality in time series J Songsiri 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 26 | 2013 |
| A comparison of deep neural networks for seizure detection in EEG signals P Boonyakitanont, A Lek-Uthai, K Chomtho, J Songsiri BioRxiv, 702654, 2019 | 23 | 2019 |
| Missing-data imputation for solar irradiance forecasting in Thailand V Layanun, S Suksamosorn, J Songsiri 2017 56th Annual Conference of the Society of Instrument and Control …, 2017 | 20 | 2017 |
| Automatic epileptic seizure onset-offset detection based on CNN in scalp EEG P Boonyakitanont, A Lek-Uthai, J Songsiri ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and …, 2020 | 17 | 2020 |
| Projection onto an ℓ 1-norm ball with application to identification of sparse autoregressive models J Songsiri Asean Symposium on Automatic Control (ASAC), 2011 | 17 | 2011 |
| Learning multiple granger graphical models via group fused lasso J Songsiri 2015 10th Asian control conference (ASCC), 1-6, 2015 | 12 | 2015 |
| Granger causality inference in EEG source connectivity analysis: a state-space approach P Manomaisaowapak, A Nartkulpat, J Songsiri IEEE Transactions on Neural Networks and Learning Systems 33 (7), 3146-3156, 2021 | 11 | 2021 |
| Dynamic models of a rotary double inverted pendulum system P Pakdeepattarakorn, P Thamvechvitee, J Songsiri, M Wongsaisuwan, ... 2004 IEEE Region 10 Conference TENCON 2004. 500, 558-561, 2004 | 11 | 2004 |
| Maximum-likelihood estimation of autoregressive models with conditional independence constraints J Songsiri, J Dahl, L Vandenberghe 2009 IEEE International Conference on Acoustics, Speech and Signal …, 2009 | 10 | 2009 |
| Convex formulation for regularized estimation of structural equation models A Pruttiakaravanich, J Songsiri Signal Processing 166, 107237, 2020 | 8 | 2020 |
| Sparse system identification for discovering brain connectivity from fMRI time series A Pongrattanakul, P Lertkultanon, J Songsiri The SICE Annual Conference 2013, 949-954, 2013 | 8 | 2013 |
| A comparison of deep neural networks for seizure detection in EEG signals. bioRxiv, 702654 P Boonyakitanont, A Lek-uthai, K Chomtho, J Songsiri | 6 | 2019 |
| Influential variable selection for improving solar forecasts from numerical weather prediction S Suksamosorn, N Hoonchareon, J Songsiri 2018 15th International Conference on Electrical Engineering/Electronics …, 2018 | 5 | 2018 |
| A review on dependence measures in exploring brain networks from fMRI data A Pruttiakaravanich, J Songsiri Engineering Journal 20 (3), 207-233, 2016 | 5 | 2016 |
| Dynamic models of servo-driven conveyor system J Songsiri, D Banjerdpongchai 2004 IEEE Region 10 Conference TENCON 2004. 500, 538-541, 2004 | 5 | 2004 |
