TRAINING ALGORITHM IN ARTIFICIAL NEURAL NETWORK (ANN) INCORPORATING NON-IDEAL MEMORY DEVICE BEHAVIOR

Machine learning of model parameters for a neural network using a computing system is provided, that produces error-aware model parameters. An iterative process to converge on trained model parameters to be applied in the inference engine, includes applying a sequence of input training data sets to a neural network to produce inference results for the sequence using a set of model parameters in the neural network combined with factors based on a model of non-ideal characteristics of target memory to provide a training set of model parameters. An inference engine using the target memory technology to store the model parameters can have more stable results across a large number of engines.