Digital implementation of a multilayer perceptron based on stochastic computing with online learning function

Abstract

Stochastic Computing (SC)[2] is a probability-based computing method, which enables the performance of various operations with a small number of logic gates (i.e., low power) in exchange for high accuracy. Using SC for edge artificial intelligence (AI) integrated circuits can help circumvent the limitations inherent in the power and area required for edge AI.

In this study, a three-layered Neural Network (NN) is presented with an online learning function that introduces pseudo-activation, pseudo-subtraction, and imperfect addition into the SC framework. This method may expand the options for edge AI integrated circuits using SC.