Building artificial CPGs with asymmetric Hopfield networks

Franca, Felipe M.G. and Yang, Zhijun ORCID: https://orcid.org/0000-0003-2615-4297 (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]

Abstract

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.

Actions (login required)

View Item

Statistics

DownloadsShow export options

Export as CSVXMLJSON

Activity Overview

6 month trend

0Downloads

6 month trend

441Hits

Additional statistics are available via IRStats2.