Stability assessment of the leech swim oscillator using a VLSI-based model

In this study VLSI-based artificial neurons are used to realize neuronal oscillatory networks. A comprehensive electronic model of the Hirudo swim oscillator is recreated and subjected to numerous parametric variations. This, combined with similar analyses of the mutually and cyclically inhibited sub-networks embedded in the network, provides a good indication of the origins of network stability. Test data indicate that different sub-network types exhibit immunity to contrasting parameters, and that the overall swim oscillator network is more stable than either sub-network type alone.