Hashemi, A. ., Lin, Y. ., McNally, W. ., Laschowski, B. ., Hosking, B. ., Wong, A. ., & McPhee, J. . (2019). Integration of Machine Learning with Dynamics and Control: From Autonomous Cars to Biomechatronics. Retrieved from http://csme-scgm.ca/sites/default/files/BULLETIN-FALL-2019.pdf
Publications
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Ghannadi, B. ., Razavian, R. S., & McPhee, J. . (2019). A Modified Homotopy Optimization for Parameter Identification in Dynamic Systems with Backlash Discontinuity. Nonlinear Dynamics, 95. https://doi.org/10.1007/s11071-018-4550-1
Razavian, R. S., Ghannadi, B. ., & McPhee, J. . (2019). On the Relationship Between Muscle Synergies and Redundant Degrees of Freedom in Musculoskeletal Systems. Frontiers in Computational Neuroscience, 13. https://doi.org/10.3389/fncom.2019.00023
Hosking, B. ., & McPhee, J. . (2018). Powertrain Modeling and Model Predictive Longitudinal Dynamics Control for Hybrid Electric Vehicles.
Hassanpour, S. ., & McPhee, J. . (2018). A Control-Oriented Modular One-Dimensional Model for Wall-Flow Diesel Particulate Filters. International Journal of Engine Research, 19. https://doi.org/10.1177/1468087417702018
Liang, Y. ., & McPhee, J. . (2018). Symbolic Integration of Multibody System Dynamics with the Finite Element Method. Multibody System Dynamics, 43. https://doi.org/10.1007/s11044-018-9627-6 (Original work published 2018)
McNally, W. ., & McPhee, J. . (2018). Dynamic Optimization of the Golf Swing Using a Six Degree-of-Freedom Biomechanical Model. 12th Conference of the International Sports Engineering Association. Presented at the. Retrieved from https://www.mdpi.com/2504-3900/2/6/243 (Original work published 2018)
Razavian, R. S., Ghannadi, B. ., & McPhee, J. . (2018). A Synergy-Based Motor Control Framework for the Fast Feedback Control of Musculoskeletal Systems. ASME Journal of Biomechanical Engineering. https://doi.org/10.1115/1.4042185
Razavian, R. S., Ghannadi, B. ., Mehrabi, N. ., Charlet, M. ., & McPhee, J. . (2018). Feedback Control of Functional Electrical Stimulation for 2D Arm Reaching Movements. IEEE Transactions on Neural Systems and Rehabilitation Engineering. https://doi.org/10.1109/TNSRE.2018.2853573
McNally, W. ., Wong, A. ., & McPhee, J. . (2018). Action Recognition using Deep Convolutional Neural Networks and Compressed Spatio-Temporal Pose Encodings. 4th Annual Conference on Vision and Intelligent Systems (CVIS). Presented at the. Retrieved from https://openjournals.uwaterloo.ca/index.php/vsl/article/view/339 (Original work published 2018)