Dynamical properties of background neural networks with uniform firing rate and background input. (English) Zbl 1127.92012
Summary: The dynamic properties of background neural networks with uniform firing rate and background input are investigated with a series of mathematical arguments including nondivergence, global attractivity and complete stability analysis. Moreover, it is shown that shifting the background level affects the existence and stability of the equilibrium point. Depending on the increase or decrease in background input, the network can engender bifurcations and chaos. It may be have one or two different stable firing levels. That means the background neural network can exhibit not only monostability but also multistability.
MSC:
| 92C20 | Neural biology |
| 37N25 | Dynamical systems in biology |
| 92B20 | Neural networks for/in biological studies, artificial life and related topics |
| 34D20 | Stability of solutions to ordinary differential equations |
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