Digitizing artificial neural networks

Most artificial neural networks are designed using an analog model derived from the McCulloch-Pitts neuron model. This design is then implemented as a simulation on a digital computer, and few designs are implemented in dedicated analog hardware. Many simulations run at a small fraction of the speed that analog hardware would allow, but custom designed analog circuitry is usually too expensive. In this paper I will introduce a digital neuron model for artificial neural networks. The purpose of this model is to simplify the design of digital neural networks and allow the design of custom hardware using common digital parts