| Fuzzy restricted Boltzmann machine for the enhancement of deep learning CLP Chen, CY Zhang, L Chen, M Gan IEEE Transactions on Fuzzy Systems 23 (6), 2163-2173, 2015 | 224 | 2015 |
| Predictive deep Boltzmann machine for multiperiod wind speed forecasting CY Zhang, CLP Chen, M Gan, L Chen IEEE Transactions on Sustainable Energy 6 (4), 1416-1425, 2015 | 208 | 2015 |
| A regularized variable projection algorithm for separable nonlinear least-squares problems GY Chen, M Gan, CLP Chen, HX Li IEEE Transactions on Automatic Control 64 (2), 526-537, 2018 | 166 | 2018 |
| On some separated algorithms for separable nonlinear least squares problems M Gan, CLP Chen, GY Chen, L Chen IEEE Transactions on Cybernetics 48 (10), 2866-2874, 2017 | 150 | 2017 |
| A novel EM identification method for Hammerstein systems with missing output data D Wang, S Zhang, M Gan, J Qiu IEEE Transactions on Industrial Informatics 16 (4), 2500-2508, 2019 | 103 | 2019 |
| A variable projection approach for efficient estimation of RBF-ARX model M Gan, HX Li, H Peng IEEE Transactions on Cybernetics 45 (3), 462-471, 2014 | 100 | 2014 |
| Fine perceptive gans for brain mr image super-resolution in wavelet domain S You, B Lei, S Wang, CK Chui, AC Cheung, Y Liu, M Gan, G Wu, Y Shen IEEE transactions on neural networks and learning systems, 2022 | 93 | 2022 |
| Diabetic retinopathy diagnosis using multichannel generative adversarial network with semisupervision S Wang, X Wang, Y Hu, Y Shen, Z Yang, M Gan, B Lei IEEE Transactions on Automation Science and Engineering 18 (2), 574-585, 2020 | 83 | 2020 |
| A locally linear RBF network-based state-dependent AR model for nonlinear time series modeling M Gan, H Peng, X Peng, X Chen, G Inoussa Information Sciences 180 (22), 4370-4383, 2010 | 78 | 2010 |
| Generalized exponential autoregressive models for nonlinear time series: Stationarity, estimation and applications G Chen, M Gan, G Chen Information Sciences 438, 46-57, 2018 | 77 | 2018 |
| A hybrid algorithm to optimize RBF network architecture and parameters for nonlinear time series prediction M Gan, H Peng, X Dong Applied Mathematical Modelling 36 (7), 2911-2919, 2012 | 70 | 2012 |
| Design a wind speed prediction model using probabilistic fuzzy system G Zhang, HX Li, M Gan IEEE Transactions on Industrial Informatics 8 (4), 819-827, 2012 | 64 | 2012 |
| Modified Gram–Schmidt method-based variable projection algorithm for separable nonlinear models GY Chen, M Gan, F Ding, CLP Chen IEEE Transactions on Neural Networks and Learning Systems 30 (8), 2410-2418, 2018 | 61 | 2018 |
| Gradient radial basis function based varying-coefficient autoregressive model for nonlinear and nonstationary time series M Gan, CLP Chen, HX Li, L Chen IEEE Signal Processing Letters 22 (7), 809-812, 2014 | 57 | 2014 |
| A novel reduced-order algorithm for rational models based on Arnoldi process and Krylov subspace J Chen, B Huang, M Gan, CLP Chen Automatica 129, 109663, 2021 | 52 | 2021 |
| Term selection for a class of separable nonlinear models M Gan, GY Chen, L Chen, CLP Chen IEEE transactions on neural networks and learning systems 31 (2), 445-451, 2019 | 49 | 2019 |
| Seasonal and trend time series forecasting based on a quasi-linear autoregressive model M Gan, Y Cheng, K Liu, G Zhang Applied soft computing 24, 13-18, 2014 | 47 | 2014 |
| Stability analysis of RBF network-based state-dependent autoregressive model for nonlinear time series M Gan, H Peng Applied Soft Computing 12 (1), 174-181, 2012 | 42 | 2012 |
| Exploiting the interpretability and forecasting ability of the RBF-AR model for nonlinear time series M Gan, CL Philip Chen, L Chen, CY Zhang International Journal of Systems Science 47 (8), 1868-1876, 2016 | 41 | 2016 |
| An efficient variable projection formulation for separable nonlinear least squares problems M Gan, HX Li IEEE transactions on cybernetics 44 (5), 707-711, 2013 | 39 | 2013 |
