Building artificial CPGs with asymmetric Hopfield networks

Franca, Felipe M.G. and Yang, Zhijun ORCID logoORCID: (2000) Building artificial CPGs with asymmetric Hopfield networks. In: The IEEE-INNS-ENNS International Joint Conference on Neural Networks (IJCNN 2000), 24-27 July 2000, Como, Italy. . [Conference or Workshop Item]


This paper presents a novel approach to the emulation of locomotor central pattern generators (CPGs) of legged animals. Based on Scheduling by Multiple Edge Reversal (SMER), a simple but powerful distributed algorithm, it is shown how oscillatory building blocks (OBBs) can be created and how OBB-based networks can be implemented as asymmetric Hopfield-like neural networks for the generation of complicatedly coordinated rhythmic patterns observed among pairs of biological motor neurons working during different gait patterns. It is also presented how a generalized CPG model mapped into such Hopfield-like networks possess some charming properties on the retrieval of a whole range of different preprogrammed gait patterns.

Item Type: Conference or Workshop Item (Paper)
Research Areas: A. > School of Science and Technology > Design Engineering and Mathematics
Item ID: 9927
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Depositing User: Zhijun Yang
Date Deposited: 05 Feb 2013 06:27
Last Modified: 09 Feb 2022 10:15

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