Filtering hidden matrix training dnn

Abstract

In one aspect, a method of training a DNN includes transmitting an input vector x through a weight matrix W and reading a resulting output vector y, transmitting an error signal δ, transmitting the input vector x with the error signal δ through conductive row wires of a matrix A, and transmitting an input vector eand reading a resulting output vector y' as current output. The training also includes updating a hidden matrix H comprising an H value for RPU devices by iteratively adding the output vector y′ multiplied by the transpose of the input vector eto each H value. The training also includes, when an H value reaches a threshold value, transmitting the input vector eas a voltage pulse through the conductive column wires of the matrix W simultaneously with sign information of the H values that reached a threshold value as voltage pulses through the conductive row wires matrix W.