Publication: Neuromorphic Implementation of Spiking Relational Neural Network for Motor Control
Neuromorphic Implementation of Spiking Relational Neural Network for Motor Control
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Zhao, J., Donati, E., & Indiveri, G. (2020). Neuromorphic Implementation of Spiking Relational Neural Network for Motor Control. 89–93. https://doi.org/10.1109/AICAS48895.2020.9073829
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Despite the rapid development of robotic control theory, hardware motor controllers still suffer from some disadvantages: they are computationally-intensive and rely on powerful computing systems which are usually implemented using bulky and power-hungry devices. On the other hand, biological motor control systems are power-efficient, light-weight and robust. Neuromorphic engineering sheds a light on how to uncover biological control features that could lead to the design of lower power and less bulky controllers. In this paper, we pr
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- Zhao, Jingyue
- Donati, Elisa
- Indiveri, Giacomo
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Zhao, J., Donati, E., & Indiveri, G. (2020). Neuromorphic Implementation of Spiking Relational Neural Network for Motor Control. 89–93. https://doi.org/10.1109/AICAS48895.2020.9073829
