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This invention addresses fixed-point representations of convolutional neuralnetworks (CNN) in integrated circuits. When quantizing a CNN for a practicalimplementation there is a trade-off between the precision used for operationsbetween coefficients and data and the accuracy of the system. A homogenousrepresentation may not be sufficient to achieve the best level of performanceat a reasonable cost in implementation complexity or power consumption.Parsimonious ways of representing data and coefficients are needed to improvepower efficiency and throughput while maintaining accuracy of a CNN.

Method for Hybrid Precision Convolutional Neural Network Representation