| 1 |
Wind missing data arrangement using wavelet based techniques for getting maximum likelihood
Zapata-Sierra AJ, Cama-Pinto A, Montoya FG, Alcayde A, Manzano-Agugliaro F
Energy Conversion and Management, 185, 552, 2019 |
| 2 |
Optimal control of electromagnetic wave displacement with an unknown velocity of propagation
Hafdallah A, Ayadi A
International Journal of Control, 92(11), 2693, 2019 |
| 3 |
A review of the Expectation Maximization algorithm in data-driven process identification
Sammaknejad N, Zhao YJ, Huang B
Journal of Process Control, 73, 123, 2019 |
| 4 |
Short-term wind speed forecasting by spectral analysis from long-term observations with missing values
Akcay H, Filik T
Applied Energy, 191, 653, 2017 |
| 5 |
Mixture semisupervised probabilistic principal component regression model with missing inputs
Sedghi S, Sadeghian A, Huang B
Computers & Chemical Engineering, 103, 176, 2017 |
| 6 |
A Missing Data Approach to Data-Driven Filtering and Control
Markovsky I
IEEE Transactions on Automatic Control, 62(4), 1972, 2017 |
| 7 |
Fault diagnosis of chemical processes with incomplete observations: A comparative study
Askarian M, Escudero G, Graells M, Zarghami R, Jalali-Farahani F, Mostoufi N
Computers & Chemical Engineering, 84, 104, 2016 |
| 8 |
Reconstruction of missing data using compressed sensing techniques with adaptive dictionary
Perepu SK, Tangirala AK
Journal of Process Control, 47, 175, 2016 |
| 9 |
Performance characteristics of a perforated shadow band in the presence of cloud
Brooks MJ, von Backstrom TW, van Dyk E
Solar Energy, 139, 533, 2016 |
| 10 |
Constrained predictive control synthesis for quantized systems with Markovian data loss
Zou YY, Lam J, Niu YG, Li DW
Automatica, 55, 217, 2015 |
