SET based Boltzmann machine and Hopfield neural networks

This paper presents a method of implementing Boltzmann machine and Hopfield neural networks using single electron devices. Comparison between these two networks is shown by computer simulations in terms of their ability to converge to a global minimum state. It is demonstrated that the probabilistic nature of single electron tunneling phenomena enables the stochastic neuron operation with Boltzmann machine.