Stochastic Radial Basis Neural Networks

Abstract

Stochastic spiking Neural Networks (SNN) is a new neural modeling oriented to include the intrinsic stochastic processes present in the brain. One of the main advantages of this kind of modeling is that they can be easily implemented in a digital circuit, thus taking advantage of this mature technology. In this paper we propose a digital design for stochastic spiking neurons oriented to high-density hardware implementation. We compare the proposal with other neural models, comparing in terms of speed, area and precision. As is shown, the circuit proposal is able to provide competitive results when comparing with other works present in the literature.