Intel Corporation
DYNAMIC COMPENSATION OF ANALOG CIRCUITRY IMPAIRMENTS IN NEURAL NETWORKS

Abstract:

Dynamic compensation of analog circuitry impairments in ANNs is provided. An example ANN includes an analog circuitry that performs MAC operations based on weights. To compensate analog circuitry impairments, a signal package including a training signal and an input signal, is formed. The training signal is fed into the ANN. The ANN generates an output signal through MAC operations by the analog circuitry with the training signal and the weights. The output signal is compared with a reference signal to determine an error in the output signal. The reference signal may include one or more ground-truth classifications of the training signal. The error is used to compute a compensation coefficient, which compensates impact of analog circuitry impairments on accuracy in outputs of the ANN. The ANN is updated with the compensation coefficient. The analog circuitry performs MAC operations with the input signal, the compensation coefficient, and the set of weights.