Patent ID: 11915132
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 14:
15. A computer program product comprising one or more computer media having computer executable instructions, which when executed by one or more processors cause the one or more processors to perform a method to train an artificial neural network (ANN), the ANN comprising a plurality of neurons arranged in layers with the outputs of one layer connected to the inputs of a plurality of the neurons of a subsequent layer, where neurons are connected to each other via a plurality of synapses, each of the synapses having a synaptic weight encoding a connection strength between two connected neurons, the magnitude of the synaptic weight of each synapse being represented by a weighted current flow from multiple conductance-pairs, where a plurality of training examples are serially input to the ANN while observing its output, where a backpropagation algorithm updates the synaptic weight in response to the difference between the output from a given layer and a desired output from the given layer, the method to train the ANN comprising:
periodically transferring a portion of the synaptic weight from a conductance-pair of lower significance to a conductance-pair of higher significance, such that the total synaptic weight remains substantially unchanged;
upon one or more of these periodic transfers of synaptic weight, inverting the polarity of the conductance-pair of lower significance; and
repeating the serial input of the training examples until the network output approaches the desired output within a predetermined accuracy.