Noise suppress or express exponential growth for hybrid Hopfield neural networks. (English) Zbl 1236.92009
Summary: Wel show that noise can make given hybrid Hopfield neural networks, whose solutions may grow exponentially, become new stochastic hybrid Hopfield neural networks whose solutions grow at most polynomially. On the other hand, we also show that noise can make given hybrid Hopfield neural networks, whose solutions grow at most polynomially, become new stochastic hybrid Hopfield neural networks whose solutions grow exponentially. In other words, wel reveal that the noise can suppress or express exponential growth for hybrid Hopfield neural networks.
MSC:
| 92B20 | Neural networks for/in biological studies, artificial life and related topics |
| 68T05 | Learning and adaptive systems in artificial intelligence |
| 60J20 | Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) |
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