| Overview of BioCreative II gene mention recognition L Smith, LK Tanabe, RJ Ando, CJ Kuo, IF Chung, CN Hsu, YS Lin, ... Genome biology 9, 1-19, 2008 | 561 | 2008 |
| Induction machine broken bar and stator short-circuit fault diagnostics based on three-phase stator current envelopes AM Da Silva, RJ Povinelli, NAO Demerdash IEEE Transactions on Industrial Electronics 55 (3), 1310-1318, 2008 | 318 | 2008 |
| Time series classification using Gaussian mixture models of reconstructed phase spaces RJ Povinelli, MT Johnson, AC Lindgren, J Ye IEEE Transactions on Knowledge and Data Engineering 16 (6), 779-783, 2004 | 226 | 2004 |
| Analyzing logistic map pseudorandom number generators for periodicity induced by finite precision floating-point representation KJ Persohn, RJ Povinelli Chaos, Solitons & Fractals 45 (3), 238-245, 2012 | 177 | 2012 |
| A new temporal pattern identification method for characterization and prediction of complex time series events RJ Povinelli, X Feng IEEE Transactions on Knowledge and Data Engineering 15 (2), 339-352, 2003 | 148 | 2003 |
| Probabilistic anomaly detection in natural gas time series data HN Akouemo, RJ Povinelli International Journal of Forecasting 32 (3), 948-956, 2016 | 117 | 2016 |
| An adaptive Kalman filter for removing baseline wandering in ECG signals MA Mneimneh, EE Yaz, MT Johnson, RJ Povinelli 2006 Computers in Cardiology, 253-256, 2006 | 111 | 2006 |
| Diagnostics of eccentricities and bar/end-ring connector breakages in polyphase induction motors through a combination of time-series data mining and time-stepping coupled FE … JF Bangura, RJ Povinelli, NAO Demerdash, RH Brown IEEE Transactions on Industry Applications 39 (4), 1005-1013, 2003 | 111 | 2003 |
| Short-term load forecasting of natural gas with deep neural network regression GD Merkel, RJ Povinelli, RH Brown Energies 11 (8), 2008, 2018 | 105 | 2018 |
| Automatic segmentation of heart sound signals using hidden Markov models AD Ricke, RJ Povinelli, MT Johnson Computers in Cardiology, 2005, 953-956, 2005 | 105 | 2005 |
| Statistical models of reconstructed phase spaces for signal classification RJ Povinelli, MT Johnson, AC Lindgren, FM Roberts, J Ye IEEE Transactions on Signal processing 54 (6), 2178-2186, 2006 | 103 | 2006 |
| Time series data mining: Identifying temporal patterns for characterization and prediction of time series events RJ Povinelli Marquette University, 1999 | 102 | 1999 |
| Diagnostics of bar and end-ring connector breakage faults in polyphase induction motors through a novel dual track of time-series data mining and time-stepping coupled FE-state … RJ Povinelli, JF Bangura, NAO Demerdash, RH Brown IEEE Transactions on Energy Conversion 17 (1), 39-46, 2002 | 91 | 2002 |
| Speech recognition using reconstructed phase space features AC Lindgren, MT Johnson, RJ Povinelli 2003 IEEE International Conference on Acoustics, Speech, and Signal …, 2003 | 85 | 2003 |
| A reconfigurable motor for experimental emulation of stator winding interturn and broken bar faults in polyphase induction machines CC Yeh, GY Sizov, A Sayed-Ahmed, NAO Demerdash, RJ Povinelli, ... IEEE Transactions on Energy Conversion 23 (4), 1005-1014, 2008 | 84 | 2008 |
| A Reconfigurable Motor for Experimental Emulation of Stator Winding Inter-Turn and Broken Bar Faults in Polyphase Induction Machines DMI Chia-Chou Yeh, Gennadi Y. Sizov, Ahmed Sayed-Ahmed, Nabeel A. O ... IEEE International Electric Machines and Drives Conference, 1413 – 1419, 2007 | 84* | 2007 |
| Rotor Bar Fault Monitoring Method Based on Analysis of Air-gap Torques of Induction Motors AD Silva, RJ Povinelli, NOA Demerdash IEEE Transactions on Industrial Informatics 9 (4), 2274-2283, 2013 | 83 | 2013 |
| Identifying temporal patterns for characterization and prediction of financial time series events RJ Povinelli International workshop on temporal, spatial, and spatio-temporal data mining …, 2000 | 83 | 2000 |
| Data improving in time series using ARX and ANN models HN Akouemo, RJ Povinelli IEEE Transactions on Power Systems 32 (5), 3352-3359, 2017 | 81 | 2017 |
| An ensemble model of QSAR tools for regulatory risk assessment P Pradeep, RJ Povinelli, S White, SJ Merrill Journal of cheminformatics 8, 1-9, 2016 | 78 | 2016 |
Michael T. JohnsonElectrical and Computer Engineering, University of KentuckyZweryfikowany adres z uky.edu
