Quantization of neural network parameters
AssigneeFujitsu Limited
InventorsMasaya KIBUNE, Xuan TAN
Life of this patent
Estimating the term…
Abstract
A method of generating a neural network may be provided. A method may include applying non-linear quantization to a plurality of synaptic weights of a neural network model. The method may further include training the neural network model. Further, the method ma include generating a neural network output from the trained neural network model based on or more inputs received by the trained neural network model.
Claims20
A method of operating a neural network, comprising:
- applying, via at least one processor, non-linear quantization to a plurality of synaptic weights of a neural network model;
- training, via the at least one processor, the neural network model;
- and
- generating, via the at least one processor, a neural network output from the trained neural network model based on or more inputs received by the trained neural network model.
One or more non-transitory computer-readable media that include instructions that, when executed by one or more processors, are configured to cause the one or more processors to perform operations, the operations comprising:
- applying non-linear quantization to a plurality of synaptic weights of a neural network model;
- training the neural network model;
- and
- generating a neural network output from the trained neural network model based on or more inputs received by the trained neural network model.
Dependencies are inferred from the claim text.