抄録
In this paper, we proposed a new hormonal-based Hopfield model neural network which is based on the idea of the homeostasis control of hormones. The network consists of a traditional Hopfield network and an evaluation network. The traditional Hopfield model network works depending on their initial states. We describe a conception of hormones to reset the initial states. A hormonal-based 4-bit Hopfield neural Analogto-Digital converter is designed and simulated by C language. Simulation shows that the local minima of the Hopfield model A/D converter can be eliminated by controlling the hormonal value. The hormonal-based Hopfield neural A/D converter performs A/D conversion much better than the traditional Hopfield model A/D converter. Furthermore, some interesting biological internal secretion phenomena are simulated and several experimentally testable predictions are made.
