| Bayesian estimation via sequential Monte Carlo sampling—Constrained dynamic systems L Lang, W Chen, BR Bakshi, PK Goel, S Ungarala Automatica 43 (9), 1615-1622, 2007 | 138 | 2007 |
| Computing arrival cost parameters in moving horizon estimation using sampling based filters S Ungarala Journal of process control 19 (9), 1576-1588, 2009 | 102 | 2009 |
| Bayesian estimation via sequential Monte Carlo sampling: unconstrained nonlinear dynamic systems W Chen, BR Bakshi, PK Goel, S Ungarala Industrial & engineering chemistry research 43 (14), 4012-4025, 2004 | 94 | 2004 |
| Constrained extended Kalman filter for nonlinear state estimation S Ungarala, E Dolence, K Li IFAC Proceedings Volumes 40 (5), 63-68, 2007 | 86 | 2007 |
| Batch scheme recursive parameter estimation of continuous-time systems using the modulating functions method TB Co, S Ungarala Automatica 33 (6), 1185-1191, 1997 | 46 | 1997 |
| On the iterated forms of Kalman filters using statistical linearization S Ungarala Journal of Process Control 22 (5), 935-943, 2012 | 33 | 2012 |
| Bayesian estimation of unconstrained nonlinear dynamic systems via sequential Monte Carlo sampling WS Chen, BR Bakshi, PK Goel, S Ungarala Industrial & Engineering Chemistry Research 43 (14), 4012-4025, 2004 | 31 | 2004 |
| A multiscale, Bayesian and error-in-variables approach for linear dynamic data rectification S Ungarala, BR Bakshi Computers & Chemical Engineering 24 (2-7), 445-451, 2000 | 23 | 2000 |
| Time-varying system identification using modulating functions and spline models with application to bio-processes S Ungarala, TB Co Computers & Chemical Engineering 24 (12), 2739-2753, 2000 | 21 | 2000 |
| Bayesian state estimation of nonlinear systems using approximate aggregate Markov chains S Ungarala, Z Chen, K Li Industrial & engineering chemistry research 45 (12), 4208-4221, 2006 | 19 | 2006 |
| A direct sampling particle filter from approximate conditional density function supported on constrained state space S Ungarala Computers & chemical engineering 35 (6), 1110-1118, 2011 | 17 | 2011 |
| Constrained Bayesian state estimation using a cell filter S Ungarala, K Li, Z Chen Industrial & engineering chemistry research 47 (19), 7312-7322, 2008 | 17 | 2008 |
| Nonlinear model predictive control based on sequential Monte Carlo state estimation SK Botchu, S Ungarala IFAC Proceedings Volumes 40 (5), 29-34, 2007 | 13 | 2007 |
| Multiscale bayesian estimation and data rectification S Ungarala, BR Bakshi Wavelets in Signal and Image Analysis: From Theory to Practice, 69-110, 2001 | 9 | 2001 |
| Bayesian estimation of unconstrained nonlinear dynamic systems W Chen, BR Bakshi, PK Goel, S Ungarala IFAC Proceedings Volumes 37 (1), 263-268, 2004 | 6 | 2004 |
| On the estimation of time-varying parameters in continuous-time nonlinear systems S Ungarala, K Miriyala, TB Co IFAC Proceedings Volumes 46 (32), 565-570, 2013 | 5 | 2013 |
| The use of a cell filter for state estimation in closed-loop NMPC of low dimensional systems S Ungarala, K Li Journal of Process Control 19 (3), 550-556, 2009 | 5 | 2009 |
| Bayesian rectification of nonlinear dynamic processes by the weighted bootstrap WS Chen, S Ungarala, B Bakshi, P Goel AIChE Annual Meeting, Reno, Nevada, 2001 | 5 | 2001 |
| Bayesian data rectification of nonlinear systems with chains in cell space S Ungarala, Z Chen Proceedings of the 2003 American Control Conference, 2003. 6, 4857-4862, 2003 | 4 | 2003 |
| Bayesian cell filter for constrained non-Gaussian estimation S Ungarala, Z Chen Proceedings of the 2004 American Control Conference 1, 216-221, 2004 | 3 | 2004 |
