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Publications of Silvia Ferrari    :chronological  alphabetical  combined  bibtex listing:

Book Chapters

  1. C. H.l Dagli et. al, Adaptive Control of Chaos Induced Capsizing of a Ship, in Intelligent Engineering Systems through Artificial Neural Networks, Fuzzy Logic and Evolutionary Progr., vol. 5 (1995), ASME Press NY
  2. Ferrari, S., Stengel, R. F., Model-based Adaptive Critic Designs, in Learning and Approximate Dynamic Programming: Scaling Up to the Real World, edited by J. Si, A. Barto, W. Powell, D. Wunsch (2004), IEEE Press and John Wiley & Sons

Papers Published

  1. Zhu, P; Liu, C; Ferrari, S, Adaptive Online Distributed Optimal Control of Very-Large-Scale Robotic Systems, Ieee Transactions on Control of Network Systems (January, 2021) [doi]  [abs]
  2. Ferrari, S; Wettergren, T; Linares, R; Legrand, K, Guest Editorial Special Issue on Control of Very-large Scale Robotic (VLSR) Networks, Ieee Transactions on Control of Network Systems (January, 2021) [doi]  [abs]
  3. Doerr, B; Linares, R; Zhu, P; Ferrari, S, Random finite set theory and centralized control of large collaborative swarms, Journal of Guidance, Control, and Dynamics, vol. 44 no. 3 (January, 2021), pp. 505-521 [doi]  [abs]
  4. Tilmon, B; Jain, E; Ferrari, S; Koppal, SJ, Fast Foveating Cameras for Dense Adaptive Resolution, Ieee Transactions on Pattern Analysis and Machine Intelligence (January, 2021) [doi]  [abs]
  5. Clawson, TS; Ferrari, S; Helbling, EF; Wood, RJ; Fu, B; Ruina, A; Wang, ZJ, Full flight envelope and trim map of flapping-wing micro aerial vehicles, Journal of Guidance, Control, and Dynamics, vol. 43 no. 12 (January, 2020), pp. 2218-2236 [doi]  [abs]
  6. Toader, AC; Rao, HM; Ryoo, M; Bohlen, MO; Cruger, JS; Oh-Descher, H; Ferrari, S; Egner, T; Beck, J; Sommer, MA, Probabilistic inferential decision-making under time pressure in rhesus macaques (Macaca mulatta)., Journal of Comparative Psychology, vol. 133 no. 3 (August, 2019), pp. 380-396 [doi]  [abs]
  7. Zhu, P; Ferrari, S; Morelli, J; Linares, R; Doerr, B, Scalable Gas Sensing, Mapping, and Path Planning via Decentralized Hilbert Maps., Sensors (Basel, Switzerland), vol. 19 no. 7 (March, 2019) [doi]  [abs]
  8. Wei, H; Zhu, P; Liu, M; How, JP; Ferrari, S, Automatic pan-tilt camera control for learning Dirichlet Process Gaussian Process (DPGP) mixture models of multiple moving targets, Ieee Transactions on Automatic Control, vol. 64 no. 1 (January, 2019), pp. 159-173, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  9. Gemerek, J; Ferrari, S; Wang, BH; Campbell, ME, Video-guided Camera Control for Target Tracking and Following, Ifac Papersonline, vol. 51 no. 34 (January, 2019), pp. 176-183 [doi]  [abs]
  10. Foderaro, G; Zhu, P; Wei, H; Wettergren, TA; Ferrari, S, Distributed Optimal Control of Sensor Networks for Dynamic Target Tracking, Ieee Transactions on Control of Network Systems, vol. 5 no. 1 (March, 2018), pp. 142-153, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  11. Zhang, X; Foderaro, G; Henriquez, C; Ferrari, S, A Scalable Weight-Free Learning Algorithm for Regulatory Control of Cell Activity in Spiking Neuronal Networks., International Journal of Neural Systems, vol. 28 no. 2 (March, 2018), pp. 1750015 [doi]  [abs]
  12. Oh-Descher, H; Beck, JM; Ferrari, S; Sommer, MA; Egner, T, Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration., Neuroimage, vol. 162 (November, 2017), pp. 138-150 [doi]  [abs]
  13. Rudd, K; Foderaro, G; Zhu, P; Ferrari, S, A generalized reduced gradient method for the optimal control of very-large-scale robotic systems, Ieee Transactions on Robotics, vol. 33 no. 5 (October, 2017), pp. 1226-1232, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  14. Foderaro, G; Swingler, A; Ferrari, S, A model-based approach to optimizing Ms. Pac-Man game strategies in real time, Ieee Transactions on Computational Intelligence and Ai in Games, vol. 9 no. 2 (June, 2017), pp. 153-165, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  15. Oh, H; Beck, JM; Zhu, P; Sommer, MA; Ferrari, S; Egner, T, Satisficing in split-second decision making is characterized by strategic cue discounting., J Exp Psychol Learn Mem Cogn, vol. 42 no. 12 (December, 2016), pp. 1937-1956 [doi]  [abs]
  16. Wei, H; Lu, W; Zhu, P; Ferrari, S; Liu, M; Klein, RH; Omidshafiei, S; How, JP, Information value in nonparametric Dirichlet-process Gaussian-process (DPGP) mixture models, Automatica, vol. 74 (December, 2016), pp. 360-368, Elsevier BV [doi]  [abs]
  17. Mazumder, P; Hu, D; Ebong, I; Zhang, X; Xu, Z; Ferrari, S, Digital implementation of a virtual insect trained by spike-timing dependent plasticity, Integration, the Vlsi Journal, vol. 54 (June, 2016), pp. 109-117, Elsevier BV [doi]  [abs]
  18. Ferrari, S; Foderaro, G; Zhu, P; Wettergren, TA, Distributed Optimal Control of Multiscale Dynamical Systems: A Tutorial, Ieee Control Systems, vol. 36 no. 2 (April, 2016), pp. 102-116, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  19. Albertson, JD; Harvey, T; Foderaro, G; Zhu, P; Zhou, X; Ferrari, S; Amin, MS; Modrak, M; Brantley, H; Thoma, ED, A Mobile Sensing Approach for Regional Surveillance of Fugitive Methane Emissions in Oil and Gas Production., Environmental Science & Technology, vol. 50 no. 5 (March, 2016), pp. 2487-2497 [doi]  [abs]
  20. Lu, W; Zhu, P; Ferrari, S, A hybrid-adaptive dynamic programming approach for the model-free control of nonlinear switched systems, Ieee Transactions on Automatic Control, vol. 61 no. 10 (January, 2016), pp. 3203-3208, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  21. Wei, H; Ferrari, S, A geometric transversals approach to sensor motion planning for tracking maneuvering targets, Ieee Transactions on Automatic Control, vol. 60 no. 10 (October, 2015), pp. 2773-2778, Institute of Electrical and Electronics Engineers (IEEE) [doi]  [abs]
  22. Rudd, K; Ferrari, S, A constrained integration (CINT) approach to solving partial differential equations using artificial neural networks, Neurocomputing, vol. 155 (January, 2015), pp. 277-285 [doi]  [abs]
  23. Wei, H; Ferrari, S, A geometric transversals approach to analyzing the probability of track detection for maneuvering targets, Ieee Transactions on Computers, vol. 63 no. 11 (November, 2014), pp. 2633-2646, Institute of Electrical and Electronics Engineers (IEEE), ISSN 0018-9340 [doi]  [abs]
  24. Rudd, K; Di Muro, G; Ferrari, S, A constrained backpropagation approach for the adaptive solution of partial differential equations., Ieee Transactions on Neural Networks and Learning Systems, vol. 25 no. 3 (March, 2014), pp. 571-584, ISSN 2162-237X [doi]  [abs]
  25. Lu, W; Zhang, G; Ferrari, S, An information potential approach to integrated sensor path planning and control, Ieee Transactions on Robotics, vol. 30 no. 4 (January, 2014), pp. 919-934, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1552-3098 [doi]  [abs]
  26. Rudd, K; Albertson, JD; Ferrari, S, Optimal root profiles in water-limited ecosystems, Advances in Water Resources, vol. 71 (January, 2014), pp. 16-22, Elsevier BV, ISSN 0309-1708 [doi]  [abs]
  27. Lu, W; Zhang, G; Ferrari, S; Anderson, M; Fierro, R, A particle-filter information potential method for tracking and monitoring maneuvering targets using a mobile sensor agent, The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, vol. 11 no. 1 (January, 2014), pp. 47-58, SAGE Publications, ISSN 1548-5129 [doi]  [abs]
  28. Foderaro, G; Ferrari, S; Wettergren, TA, Distributed optimal control for multi-agent trajectory optimization, Automatica, vol. 50 no. 1 (January, 2014), pp. 149-154, ISSN 0005-1098 [doi]  [abs]
  29. Zielinski, DJ; McMahan, RP; Lu, W; Ferrari, S, ML2VR: Providing MATLAB users an easy transition to virtual reality and immersive interactivity, Proceedings Ieee Virtual Reality (October, 2013), pp. 83-84, IEEE [doi]  [abs]
  30. Ferrari, S; Rudd, K; Di Muro, G, A Constrained Backpropagation Approach to Function Approximation and Approximate Dynamic Programming (February, 2013), pp. 162-181, JOHN WILEY & SONS INC [doi]  [abs]
  31. Zhang, X; Xu, Z; Henriquez, C; Ferrari, S, Spike-based indirect training of a spiking neural network-controlled virtual insect, Proceedings of the Ieee Conference on Decision and Control (January, 2013), pp. 6798-6805, IEEE, ISSN 0191-2216 [doi]  [abs]
  32. Wei, H; Ross, W; Varisco, S; Krief, P; Ferrari, S, Modeling of human driver behavior via receding horizon and artificial neural network controllers, Proceedings of the Ieee Conference on Decision and Control (January, 2013), pp. 6778-6785, IEEE, ISSN 0191-2216 [doi]  [abs]
  33. Swingler, A; Ferrari, S, On the duality of robot and sensor path planning, Proceedings of the Ieee Conference on Decision and Control (January, 2013), pp. 984-989, IEEE, ISSN 0191-2216 [doi]  [abs]
  34. Rudd, K; Foderaro, G; Ferrari, S, A generalized reduced gradient method for the optimal control of multiscale dynamical systems, Proceedings of the Ieee Conference on Decision and Control (January, 2013), pp. 3857-3863, IEEE, ISSN 0191-2216 [doi]  [abs]
  35. Lu, W; Ferrari, S, An approximate dynamic programming approach for model-free control of switched systems, Proceedings of the Ieee Conference on Decision and Control (January, 2013), pp. 3837-3844, IEEE, ISSN 0191-2216 [doi]  [abs]
  36. Zielinski, D; Kopper, R; McMahan, RP; Lu, W; Ferrari, S, Intercept Tags: Enhancing Intercept-based Systems, Virtual Reality Software and Technology, 2013 Acm Symposium On (2013), pp. 263-266, ACM Press [doi]  [abs]
  37. Foderaro, G; Ferrari, S; Wettergren, TA, Distributed optimal control for multi-agent trajectory optimization, Automatica (2013), ISSN 0005-1098
  38. Tolic, D; Fierro, R; Ferrari, S, Optimal self-triggering for nonlinear systems via Approximate Dynamic Programming, Proceedings of the Ieee International Conference on Control Applications (December, 2012), pp. 879-884, IEEE [doi]  [abs]
  39. Foderaro, G; Swingler, A; Ferrari, S, A model-based cell decomposition approach to on-line pursuit-evasion path planning and the video game Ms. Pac-Man, 2012 Ieee Conference on Computational Intelligence and Games, Cig 2012 (December, 2012), pp. 281-287, IEEE [doi]  [abs]
  40. Zhang, G; Ferrari, S; Cai, C, A comparison of information functions and search strategies for sensor planning in target classification., Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society, vol. 42 no. 1 (February, 2012), pp. 2-16 [22057064], [doi]  [abs]
  41. Ferrari, S; Daugherty, G, A Q-learning approach to automated unmanned air vehicle demining, The Journal of Defense Modeling and Simulation: Applications, Methodology, Technology, vol. 9 no. 1 (January, 2012), pp. 83-92, SAGE Publications, ISSN 1548-5129 [doi]  [abs]
  42. Maheswaranathan, N; Ferrari, S; Vandongen, AMJ; Henriquez, CS, Emergent bursting and synchrony in computer simulations of neuronal cultures., Frontiers in Computational Neuroscience, vol. 6 (2012), pp. 15 [22514531], [doi]  [abs]
  43. Ferrari, S; Anderson, M; Fierro, R; Lu, W, Cooperative navigation for heterogeneous autonomous vehicles via approximate dynamic programming, Proceedings of the Ieee Conference on Decision and Control (December, 2011), pp. 121-127, IEEE, ISSN 0191-2216 [doi]  [abs]
  44. Foderaro, G; Raju, V; Ferrari, S, A cell decomposition approach to online evasive path planning and the video game Ms. Pac-Man, Ieee International Symposium on Intelligent Control Proceedings (November, 2011), pp. 191-197, IEEE [doi]  [abs]
  45. Lu, W; Zhang, G; Ferrari, S; Fierro, R; Palunko, I, An information potential approach for tracking and surveilling multiple moving targets using mobile sensor agents, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 8045 (September, 2011), SPIE, ISSN 0277-786X [doi]  [abs]
  46. Foderaro, G; Raju, V; Ferrari, S, A model-based approximate λ-policy iteration approach to online evasive path planning and the video game Ms. Pac-Man, Journal of Control Theory and Applications, vol. 9 no. 3 (August, 2011), pp. 391-399, Springer Nature, ISSN 1672-6340 [doi]  [abs]
  47. Ferrari, S; Sarangapani, J; Lewis, FL, Special issue on approximate dynamic programming and reinforcement learning, Journal of Control Theory and Applications, vol. 9 no. 3 (August, 2011), pp. 309, Springer Nature, ISSN 1672-6340 [doi]
  48. Bezzo, N; Fierro, R; Swingler, A; Ferrari, S, A disjunctive programming approach for motion planning of mobile router networks, International Journal of Robotics and Automation, vol. 26 no. 1 (March, 2011), pp. 13-25, ACTA Press, ISSN 0826-8185 [doi]  [abs]
  49. Ferrari, S; Zhang, G; Wettergren, TA, Probabilistic track coverage in cooperative sensor networks., Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society, vol. 40 no. 6 (December, 2010), pp. 1492-1504 [20236903], [doi]  [abs]
  50. Ferrari, S; Foderaro, G, A potential field approach to finding minimum-exposure paths in wireless sensor networks, Proceedings Ieee International Conference on Robotics and Automation (August, 2010), pp. 335-341, IEEE, ISSN 1050-4729 [doi]  [abs]
  51. Ferrari, S; Foderaro, G; Tremblay, A, A probability density function approach to distributed sensors' path planning, Proceedings Ieee International Conference on Robotics and Automation (August, 2010), pp. 432-439, IEEE, ISSN 1050-4729 [doi]  [abs]
  52. Ferrari, S; Daugherty, G, Q-learning approach to automated Unmanned Air Vehicle (UAV) demining, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 7692 (June, 2010), SPIE, ISSN 0277-786X [doi]  [abs]
  53. Foderaro, G; Henriquez, C; Ferrari, S, Indirect training of a spiking neural network for flight control via spike-timing-dependent synaptic plasticity, Proceedings of the Ieee Conference on Decision and Control (January, 2010), pp. 911-917, IEEE, ISSN 0191-2216 [doi]  [abs]
  54. Swingler, A; Ferrari, S, A cell decomposition approach to cooperative path planning and collision avoidance via disjunctive programming, Proceedings of the Ieee Conference on Decision and Control (January, 2010), pp. 6329-6336, IEEE, ISSN 0191-2216 [doi]  [abs]
  55. Bernard, B; Ferrari, S, A geometric transversals approach to analyzing track coverage of omnidirectional sensor networks for maneuvering targets, Proceedings of the Ieee Conference on Decision and Control (January, 2010), pp. 1243-1249, IEEE, ISSN 0191-2216 [doi]  [abs]
  56. Foderaro, G; Ferrari, S, Necessary conditions for optimality for a distributed optimal control problem, Proceedings of the Ieee Conference on Decision and Control (January, 2010), pp. 4831-4838, IEEE, ISSN 0191-2216 [doi]  [abs]
  57. Lu, W; Zhang, G; Ferrari, S, A randomized hybrid system approach to coordinated robotic sensor planning, Proceedings of the Ieee Conference on Decision and Control (January, 2010), pp. 3857-3864, IEEE, ISSN 0191-2216 [doi]  [abs]
  58. Ferrari, S; Fierro, R; Tolic, D, A geometric optimization approach to tracking maneuvering targets using a heterogeneous mobile sensor network, Proceedings of the Ieee Conference on Decision and Control (December, 2009), pp. 1080-1087, IEEE, ISSN 0191-2216 [doi]  [abs]
  59. Di Muro, G; Ferrari, S, A constrained backpropagation approach to solving Partial Differential Equations in non-stationary environments, Proceedings of the International Joint Conference on Neural Networks (November, 2009), pp. 685-689, IEEE [doi]  [abs]
  60. Baumgartner, KAC; Ferrari, S; Rao, AV, Optimal control of an underwater sensor network for cooperative target tracking, Ieee Journal of Oceanic Engineering, vol. 34 no. 4 (November, 2009), pp. 678-697, Institute of Electrical and Electronics Engineers (IEEE), ISSN 0364-9059 [doi]  [abs]
  61. Baumgartner, KAC; Ferrari, S; Wettergren, TA, Robust deployment of dynamic sensor networks for cooperative track detection, Ieee Sensors Journal, vol. 9 no. 9 (September, 2009), pp. 1029-1048, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1530-437X [doi]  [abs]
  62. Zhang, G; Ferrari, S; Qian, M, An information roadmap method for robotic sensor path planning, Journal of Intelligent and Robotic Systems, vol. 56 no. 1-2 (September, 2009), pp. 69-98, Springer Nature, ISSN 0921-0296 [doi]  [abs]
  63. Ferrari, S; Cai, C, Information-driven search strategies in the board game of CLUE., Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society, vol. 39 no. 3 (June, 2009), pp. 607-625 [19174352], [doi]  [abs]
  64. Cai, C; Ferrari, S, Information-driven sensor path planning by approximate cell decomposition., Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society, vol. 39 no. 3 (June, 2009), pp. 672-689 [19193512], [doi]  [abs]
  65. Ferrari, S, Multiobjective algebraic synthesis of neural control systems by implicit model following., Ieee Transactions on Neural Networks, vol. 20 no. 3 (March, 2009), pp. 406-419 [19203887], [doi]  [abs]
  66. Ferrari, S; Fierro, R; Perteet, B; Cai, C; Baumgartner, K, A geometric optimization approach to detecting and intercepting dynamic targets using a mobile sensor network, Siam Journal on Control and Optimization, vol. 48 no. 1 (January, 2009), pp. 292-320, Society for Industrial & Applied Mathematics (SIAM), ISSN 0363-0129 [doi]  [abs]
  67. Zhang, G; Ferrari, S, An adaptive artificial potential function approach for geometric sensing, Proceedings of the Ieee Conference on Decision and Control (January, 2009), pp. 9703-9708, IEEE, ISSN 0191-2216 [doi]  [abs]
  68. Fierro, R; Ferrari, S; Cai, C, An information-driven framework for motion planning in robotic sensor networks: Complexity and experiments, Proceedings of the Ieee Conference on Decision and Control (December, 2008), pp. 483-489, IEEE, ISSN 0191-2216 [doi]  [abs]
  69. Di Muro, G; Ferrari, S, A constrained-optimization approach to training neural networks for smooth function approximation and system identification, Proceedings of the International Joint Conference on Neural Networks (November, 2008), pp. 2353-2359, IEEE [doi]  [abs]
  70. Ferrari, S; Mehta, B; Di Muro, G; VanDongen, AMJ; Henriquez, C, Biologically realizable reward-modulated hebbian training for spiking neural networks, Proceedings of the International Joint Conference on Neural Networks (November, 2008), pp. 1780-1786, IEEE [doi]  [abs]
  71. Cai, C; Ferrari, S, A Q-learning approach to developing an automated neural computer player for the board game of CLUE®, Proceedings of the International Joint Conference on Neural Networks (November, 2008), pp. 2346-2352, IEEE [doi]  [abs]
  72. Baumgartner, K; Ferrari, S; Palermo, G, Constructing Bayesian networks for criminal profiling from limited data, Knowledge Based Systems, vol. 21 no. 7 (October, 2008), pp. 563-572, Elsevier BV, ISSN 0950-7051 (Available online at: http://dx.doi.org/10.1016/j.knosys.2008.03.019.) [doi]  [abs]
  73. Ferrari, S; Steck, JE; Chandramohan, R, Adaptive feedback control by constrained approximate dynamic programming., Ieee Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the Ieee Systems, Man, and Cybernetics Society, vol. 38 no. 4 (August, 2008), pp. 982-987 [18632388], [doi]  [abs]
  74. Baumgartner, K; Ferrari, S, A geometric transversal approach to analyzing track coverage in sensor networks, Ieee Transactions on Computers, vol. 57 no. 8 (August, 2008), pp. 1113-1128, Institute of Electrical and Electronics Engineers (IEEE), ISSN 0018-9340 [doi]  [abs]
  75. Ferrari, S; Jensenius, M, A constrained optimization approach to preserving prior knowledge during incremental training., Ieee Transactions on Neural Networks, vol. 19 no. 6 (June, 2008), pp. 996-1009, ISSN 1045-9227 [18541500], [doi]  [abs]
  76. Bruzzone, R; Strano, M; Palermo, G; Baumgartner, KC; Ferrari, S, Network Models of Criminal Behavior, Ieee Control Systems, vol. 28 no. 4 (January, 2008), pp. 65-77, Institute of Electrical and Electronics Engineers (IEEE), ISSN 0888-0611 [doi]  [abs]
  77. Ferrari, S., Stengel, R. F., Classical/Neural Synthesis of Nonlinear Control Systems, Journal of Guidance, Control, and Dynamics, vol. 25 no. 3 (May-June 2002), pp. 442-448
  78. Ferrari, S., Stengel, R. F., On-line Adaptive Critic Flight Control, Journal of Guidance, Control, and Dynamics, vol. 27 no. 5 (Sept-Oct 2004), pp. 777-786
  79. Ferrari, S., Stengel, R. F., Smooth Function Approximation by Neural Networks, IEEE Transactions on Neural Networks, vol. 16 no. 1 (January 2005), pp. 24-38
  80. Ferrari, S., Vaghi, A., Demining Sensor Modeling and Feature-level Fusion by Bayesian Networks, IEEE Sensors Journal, vol. 6 no. 2 (April 2006), pp. 471-483
  81. Crews B. K., Ferrari, S., Salfati, C. G., Bayesian Network Modeling of Offender Behavior for Criminal Profiling, Proc. of the 44th IEEE Conference on Decision and Control, and the European Control Conference (December 12-15, 2005), pp. 2702-2709 (Seville, Spain.)
  82. S. Ferrari, Track Coverage in Sensor Networks, Proc. of the 2006 American Control Conference, Minneapolis, MN (June 2006), pp. 2053-2059
  83. Cai, C., and Ferrari, S., On the Development of an Intelligent Computer Player for CLUE®, the Great Detective Boardgame: A Case Study in Preposterior Decision Analysis, Proc. of the 2006 American Control Conference, Minneapolis, MN (June 2006), pp. 4350-4355
  84. Baumgartner, K. C., and Ferrari, S., Optimal Control of a Moving Sensor Network for Track Coverage, Proc. of the 2007 American Control Conference, New York, NY (July 2007), pp. 4040-4046
  85. Ferrari, S., Cai, C., Fierro, R., and Perteet, B., A Multi-Objective Optimization Approach to Detecting and Tracking Dynamic Targets in Pursuit-Evasion Games, Proc. of the 2007 American Control Conference, New York, NY (July 2007), pp. 5316-5321
  86. Ferrari, S., and Jensenius M., A Constrained Optimization Approach to Preserving Prior Knowledge During Incremental Training, IEEE Transactions on Neural Networks, vol. 19 no. 6 (June 2008)
  87. Ferrari, S; Fierro, R; Perteet, B; Cai, C; Baumgartner, KC, A Multi-Objective Optimization Approach to Detecting and Intercepting Dynamic Targets Using Mobile Sensors, Siam Journal on Control and Optimization (2008)
  88. Cai, C; Ferrari, S, Comparison of information-theoretic objective functions for decision support in sensor systems, Proceedings of the American Control Conference (December, 2007), pp. 3559-3564, IEEE, ISSN 0743-1619 [doi]  [abs]
  89. Baumgartner, K; Ferrari, S, Optimal placement of a moving sensor network for track coverage, Proceedings of the American Control Conference (December, 2007), pp. 4040-4046, IEEE, ISSN 0743-1619 [doi]  [abs]
  90. Ferrari, S; Cai, C; Fierro, R; Perteet, B, A geometric optimization approach to detecting and intercepting dynamic targets, Proceedings of the American Control Conference (December, 2007), pp. 5316-5321, IEEE, ISSN 0743-1619 [doi]  [abs]
  91. Cai, C; Ferrari, S; Qian, M, Bayesian network modeling of acoustic sensor measurements, Proceedings of Ieee Sensors (December, 2007), pp. 345-348, IEEE [doi]  [abs]
  92. Chandramohan, R; Steck, JE; Rokhsaz, K; Ferrari, S, Adaptive critic flight control for a general aviation aircraft: Simulations for the beech bonanza fly-by-wire test bed, Collection of Technical Papers 2007 Aiaa Infotech at Aerospace Conference, vol. 1 (January, 2007), pp. 840-855 [doi]  [abs]
  93. Cai, C; Ferrari, S, On the development of an intelligent computer player for CLUE®: A case study on preposterior decision analysis, Proceedings of the American Control Conference, vol. 2006 (December, 2006), pp. 4350-4355, ISSN 0743-1619  [abs]
  94. S. Ferrari and A. Vaghi, Demining sensor modeling and feature-level fusion by Bayesian networks, Ieee Sensors Journal, vol. 6 no. 2 (April, 2006), pp. 471 -- 483, ISSN 1530-437X
  95. Ferrari, S; Vaghi, A, Demining sensor modeling and feature-level fusion by bayesian networks, Ieee Sensors Journal, vol. 6 no. 2 (April, 2006), pp. 471-483, Institute of Electrical and Electronics Engineers (IEEE), ISSN 1530-437X [JSEN.2006.870162], [doi]  [abs]
  96. Ferrari, S, Track coverage in sensor networks, Proceedings of the American Control Conference, vol. 2006 (January, 2006), pp. 2053-2059, IEEE, ISSN 0743-1619 [doi]  [abs]
  97. Baumgartner, KC; Ferrari, S; Salfati, CG, Bayesian network modeling of offender behavior for criminal profiling, Proceedings of the 44th Ieee Conference on Decision and Control, and the European Control Conference, Cdc Ecc '05, vol. 2005 (December, 2005), pp. 2702-2709, IEEE, Seville, Spain [CDC.2005.1582571], [doi]  [abs]
  98. Qian, M; Ferrari, S, Probabilistic deployment for multiple sensor systems, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 5765 no. PART 1 (September, 2005), pp. 85-96, SPIE, San Diego, CA, United States, ISSN 0277-786X [12.601597], [doi]  [abs]
  99. S. Ferrari and R. F. Stengel, Smooth function approximation using neural networks, Ieee Transactions On Neural Networks, vol. 16 no. 1 (January, 2005), pp. 24 -- 38, ISSN 1045-9227
  100. Ferrari, S; Jensenius, M, Robust and reconfigurable flight control by neural networks, Collection of Technical Papers Infotech at Aerospace: Advancing Contemporary Aerospace Technologies and Their Integration, vol. 2 (January, 2005), pp. 1161-1166, Arlington, VA, United States [doi]  [abs]
  101. Ferrari, S; Stengel, RF, Smooth function approximation using neural networks., Ieee Transactions on Neural Networks, vol. 16 no. 1 (January, 2005), pp. 24-38, ISSN 1045-9227 [15732387], [doi]  [abs]
  102. Ferrari, S; Stengel, RF, Online adaptive critic flight control, Journal of Guidance, Control, and Dynamics, vol. 27 no. 5 (January, 2004), pp. 777-786, American Institute of Aeronautics and Astronautics (AIAA), ISSN 0731-5090 [doi]  [abs]
  103. S. Ferrari and R. F. Stengel, Online adaptive critic flight control, Journal Of Guidance Control And Dynamics, vol. 27 no. 5 (2004), pp. 777 -- 786, ISSN 0731-5090
  104. Ferrari, S; Stengel, RF, Classical/neural synthesis of nonlinear control systems, Journal of Guidance, Control, and Dynamics, vol. 25 no. 3 (January, 2002), pp. 442-448, American Institute of Aeronautics and Astronautics (AIAA) [doi]  [abs]
  105. Ferrari, S; Stengel, RF, An adaptive critic global controller, Proceedings of the American Control Conference, vol. 4 (January, 2002), pp. 2665-2670, IEEE, Anchorage, AK, United States, ISSN 0743-1619 [ACC.2002.1025189], [doi]  [abs]
  106. Ferrari, S; Stengel, RF, Algebraic training of a neural network, Proceedings of the American Control Conference, vol. 2 (January, 2001), pp. 1605-1610, IEEE [doi]  [abs]
  107. Ferrari, S; Stengel, RF, Classical/neural synthesis of nonlinear control systems, Aiaa Guidance, Navigation, and Control Conference and Exhibit, vol. 25 no. 3 (December, 2000), pp. 442-448  [abs]
  108. Crispin, Y; Ferrari, S, Adaptive control of chaos induced capsizing of a ship, Intelligent Engineering Systems Through Artificial Neural Networks, vol. 5 (December, 1995), pp. 569-574, St.Louis, MO, USA  [abs]

Papers Published

  1. Yang, H; Jing, D; Tarokh, V; Bewley, G; Ferrari, S, Flow parameter estimation based on on-board measurements of air vehicle traversing turbulent flows, Aiaa Scitech 2021 Forum (January, 2021), pp. 1-10, ISBN 9781624106095  [abs]
  2. Liu, C; Liao, Z; Ferrari, S, Rumor-robust Decentralized Gaussian Process Learning, Fusion, and Planning for Modeling Multiple Moving Targets, Proceedings of the Ieee Conference on Decision and Control, vol. 2020-December (December, 2020), pp. 3066-3071, ISBN 9781728174471 [doi]  [abs]
  3. Dong, J; Zhu, P; Ferrari, S, Oriented Pedestrian Social Interaction Modeling and Inference, Proceedings of the American Control Conference, vol. 2020-July (July, 2020), pp. 1373-1380, ISBN 9781538682661 [doi]  [abs]
  4. Legrand, K; Ferrari, S, The role of bounded fields-of-view and negative information in finite set statistics (FISST), Proceedings of 2020 23rd International Conference on Information Fusion, Fusion 2020 (July, 2020), ISBN 9780578647098 [doi]  [abs]
  5. Tilmon, B; Jain, E; Ferrari, S; Koppal, S, FoveaCam: A MEMS mirror-enabled foveating camera, Ieee International Conference on Computational Photography, Iccp 2020 (April, 2020), ISBN 9781728152301 [doi]  [abs]
  6. Morelli, J; Zhu, P; Doerr, B; Linares, R; Ferrari, S, Integrated mapping and path planning for very large-scale robotic (VLSR) systems, Proceedings Ieee International Conference on Robotics and Automation, vol. 2019-May (May, 2019), pp. 3356-3362, ISBN 9781538660263 [doi]  [abs]
  7. Liu, C; Chen, Y; Gemerek, J; Yang, H; Ferrari, S, Learning recursive bayesian nonparametric modeling of moving targets via mobile decentralized sensors, Proceedings Ieee International Conference on Robotics and Automation, vol. 2019-May (May, 2019), pp. 8034-8040, ISBN 9781538660263 [doi]  [abs]
  8. Liu, C; Ferrari, S, Vision-guided planning and control for autonomous taxiing via convolutional neural networks, Aiaa Scitech 2019 Forum (January, 2019), ISBN 9781624105784 [doi]  [abs]
  9. Doerr, B; Linares, R; Zhu, P; Ferrari, S, Random finite set theory and optimal control of large spacecraft swarms, Advances in the Astronautical Sciences, vol. 168 (January, 2019), pp. 3729-3748, ISBN 9780877036593  [abs]
  10. Clawson, TS; Stewart, TC; Eliasmith, C; Ferrari, S, An adaptive spiking neural controller for flapping insect-scale robots, 2017 Ieee Symposium Series on Computational Intelligence, Ssci 2017 Proceedings, vol. 2018-January (February, 2018), pp. 1-7, IEEE, ISBN 9781538627259 [doi]  [abs]
  11. Zhu, P; Isaacs, J; Fu, B; Ferrari, S, Deep learning feature extraction for target recognition and classification in underwater sonar images, 2017 Ieee 56th Annual Conference on Decision and Control, Cdc 2017, vol. 2018-January (January, 2018), pp. 2724-2731, IEEE, ISBN 9781509028733 [doi]  [abs]
  12. Chang, S; Isaacs, J; Fu, B; Shin, J; Zhu, P; Ferrari, S, Confidence level estimation in multi-target classification problems, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 10628 (January, 2018), SPIE, ISBN 9781510617674 [doi]  [abs]
  13. Fu, B; Ferrari, S, Robust flight control via minimum H∞ entropy principle, Aiaa Guidance, Navigation, and Control Conference, 2018 no. 210039 (January, 2018), American Institute of Aeronautics and Astronautics, ISBN 9781624105265 [doi]  [abs]
  14. Gemerek, JR; Ferrari, S; Albertson, JD, Fugitive gas emission rate estimation using multiple heterogeneous mobile sensors, Isoen 2017 Isocs/Ieee International Symposium on Olfaction and Electronic Nose, Proceedings (July, 2017), IEEE, ISBN 9781509023912 [doi]  [abs]
  15. Clawson, TS; Fuller, SB; Wood, RJ; Ferrari, S, A blade element approach to modeling aerodynamic flight of an insect-scale robot, Proceedings of the American Control Conference (June, 2017), pp. 2843-2849, IEEE, ISBN 9781509059928 [doi]  [abs]
  16. Clawson, TS; Ferrari, S; Fuller, SB; Wood, RJ, Spiking neural network (SNN) control of a flapping insect-scale robot, 2016 Ieee 55th Conference on Decision and Control, Cdc 2016 (December, 2016), pp. 3381-3388, IEEE, ISBN 9781509018376 [doi]  [abs]
  17. Zhu, P; Morelli, J; Ferrari, S, Value function approximation for the control of multiscale dynamical systems, 2016 Ieee 55th Conference on Decision and Control, Cdc 2016 (December, 2016), pp. 5471-5477, IEEE, ISBN 9781509018376 [doi]  [abs]
  18. Zhu, P; Wei, H; Lu, W; Ferrari, S, Multi-kernel probability distribution regressions, Proceedings of the International Joint Conference on Neural Networks, vol. 2015-September (September, 2015), IEEE, ISBN 9781479919604 [doi]  [abs]
  19. Albertson, JD; Foster-Wittig, TA; Ferrari, S; Katul, G; Thoma, E, Bayesian estimation of methane emission rates from a single high-frequency gas sensor, Proceedings of the Air and Waste Management Association'S Annual Conference and Exhibition, Awma, vol. 1 (January, 2014), pp. 622-626, ISSN 1052-6102, ISBN 9781634397322  [abs]
  20. Hu, D; Zhang, X; Xu, Z; Ferrari, S; Mazumder, P, Digital implementation of a spiking neural network (SNN) capable of spike-timing-dependent plasticity (STDP) learning, 14th Ieee International Conference on Nanotechnology, Ieee Nano 2014 (January, 2014), pp. 873-876, IEEE, ISBN 9781479956227 [doi]  [abs]
  21. Wei, H; Lu, W; Zhu, P; Huang, G; Leonard, J; Ferrari, S, Optimized visibility motion planning for target tracking and localization, Ieee International Conference on Intelligent Robots and Systems (January, 2014), pp. 76-82, IEEE, ISSN 2153-0858, ISBN 9781479969340 [doi]  [abs]
  22. Wei, H; Lu, W; Zhu, P; Ferrari, S; Klein, RH; Omidshafiei, S; How, JP, Camera control for learning nonlinear target dynamics via Bayesian nonparametric Dirichlet-process Gaussian-process (DP-GP) models, Ieee International Conference on Intelligent Robots and Systems (January, 2014), pp. 95-102, IEEE, ISSN 2153-0858, ISBN 9781479969340 [doi]  [abs]
  23. Bellini, AC; Lu, W; Naldi, R; Ferrari, S, Information driven path planning and control for collaborative aerial robotic sensors using artificial potential functions, Proceedings of the American Control Conference (January, 2014), pp. 590-597, IEEE, ISSN 0743-1619, ISBN 9781479932726 [doi]  [abs]
  24. Lu, W; Ferrari, S; Fierro, R; Wettergren, TA, Approximate dynamic programming recurrence relations for a hybrid optimal control problem, Smart Structures and Materials 2005: Active Materials: Behavior and Mechanics, vol. 8387 (December, 2012), SPIE, ISSN 0277-786X, ISBN 9780819490650 [Gateway.cgi], [doi]  [abs]
  25. Lu, W; Zhang, G; Ferrari, S, A comparison of information theoretic functions for tracking maneuvering targets, 2012 Ieee Statistical Signal Processing Workshop, Ssp 2012 (November, 2012), pp. 149-152, IEEE, ISBN 9781467301831 [Gateway.cgi], [doi]  [abs]
  26. Ferrari, S; Stengel, RF, Classical/neural synthesis of nonlinear control systems, Aiaa Guidance, Navigation, and Control Conference and Exhibit (January, 2000), ISBN 9781563479786 [doi]  [abs]
  27. Crispin, Y; Ferrari, S, Model-reference adaptive control of chaos in periodically forced dynamical systems, 6th Symposium on Multidisciplinary Analysis and Optimization (January, 1996), pp. 882-890  [abs]