Autocompensated capacitive circuit for stochastic neural networks

Abstract

A capacitive analogue circuit for the implementation of stochastic neural networks is described. This circuit automatically compensates for parasitic effects such as charge injection and the offset of the decision unit; it is well-suited to the implementation of the learning algorithms of Boltzmann machines.