| Smooth function approximation using neural networks S Ferrari, RF Stengel IEEE Transactions on Neural Networks 16 (1), 24-38, 2005 | 396 | 2005 |
| Information-driven sensor path planning by approximate cell decomposition C Cai, S Ferrari IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 39 …, 2009 | 209 | 2009 |
| Online adaptive critic flight control S Ferrari, RF Stengel Journal of Guidance, Control, and Dynamics 27 (5), 777-786, 2004 | 163 | 2004 |
| A constrained integration (CINT) approach to solving partial differential equations using artificial neural networks K Rudd, S Ferrari Neurocomputing 155, 277-285, 2015 | 125 | 2015 |
| Deep learning feature extraction for target recognition and classification in underwater sonar images P Zhu, J Isaacs, B Fu, S Ferrari 2017 IEEE 56th annual conference on decision and control (CDC), 2724-2731, 2017 | 120 | 2017 |
| Constructing Bayesian networks for criminal profiling from limited data K Baumgartner, S Ferrari, G Palermo Knowledge-Based Systems 21 (7), 563-572, 2008 | 115 | 2008 |
| Distributed optimal control for multi-agent trajectory optimization G Foderaro, S Ferrari, TA Wettergren Automatica 50 (1), 149-154, 2014 | 89 | 2014 |
| An information roadmap method for robotic sensor path planning G Zhang, S Ferrari, M Qian Journal of Intelligent and Robotic Systems 56, 69-98, 2009 | 84 | 2009 |
| A mobile sensing approach for regional surveillance of fugitive methane emissions in oil and gas production JD Albertson, T Harvey, G Foderaro, P Zhu, X Zhou, S Ferrari, MS Amin, ... Environmental science & technology 50 (5), 2487-2497, 2016 | 81 | 2016 |
| Model-based adaptive critic designs RF Stengel, S Ferrari New York, 64-94, 2014 | 74 | 2014 |
| A geometric optimization approach to detecting and intercepting dynamic targets using a mobile sensor network S Ferrari, R Fierro, B Perteet, C Cai, K Baumgartner SIAM journal on control and optimization 48 (1), 292-320, 2009 | 67 | 2009 |
| An adaptive critic global controller S Ferrari, RF Stengel Proceedings of the 2002 American Control Conference (IEEE Cat. No. CH37301 …, 2002 | 67 | 2002 |
| A constrained backpropagation approach for the adaptive solution of partial differential equations K Rudd, G Di Muro, S Ferrari IEEE transactions on neural networks and learning systems 25 (3), 571-584, 2013 | 66 | 2013 |
| Spiking neural network (SNN) control of a flapping insect-scale robot TS Clawson, S Ferrari, SB Fuller, RJ Wood 2016 IEEE 55th Conference on Decision and Control (CDC), 3381-3388, 2016 | 63 | 2016 |
| Spike-based indirect training of a spiking neural network-controlled virtual insect X Zhang, Z Xu, C Henriquez, S Ferrari 52nd IEEE Conference on Decision and Control, 6798-6805, 2013 | 63 | 2013 |
| A constrained optimization approach to preserving prior knowledge during incremental training S Ferrari, M Jensenius IEEE Transactions on Neural Networks 19 (6), 996-1009, 2008 | 61 | 2008 |
| Optimal control of an underwater sensor network for cooperative target tracking KAC Baumgartner, S Ferrari, AV Rao IEEE Journal of Oceanic Engineering 34 (4), 678-697, 2009 | 59 | 2009 |
| Demining sensor modeling and feature-level fusion by Bayesian networks S Ferrari, A Vaghi IEEE Sensors Journal 6 (2), 471-483, 2006 | 59 | 2006 |
| Bayesian network modeling of offender behavior for criminal profiling KC Baumgartner, S Ferrari, CG Salfati Proceedings of the 44th IEEE Conference on Decision and Control, 2702-2709, 2005 | 57 | 2005 |
| Adaptive feedback control by constrained approximate dynamic programming S Ferrari, JE Steck, R Chandramohan IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 38 …, 2008 | 55 | 2008 |
