Patent · US Active

Training of artificial neural networks

US11531898B2 · kind B2 · utility

1Cited by
1References
25Claims
0Family size

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Inventors

Key dates

Filing dateMay 16, 2019
Grant dateDec 20, 2022
Priority date
Expiry dateOct 20, 2041

Classification

  • Technology area (CPC G)Physics
  • CPC primaryG06N3/048
  • WIPO fieldComputer technology
  • WIPO sectorElectrical engineering

Abstract

Methods and apparatus are provided for training an artificial neural network having a succession of neuron layers with interposed synaptic layers each having a respective set of N-bit fixed-point weights {w} for weighting signals propagated between its adjacent neuron layers, via an iterative cycle of signal propagation and weight-update calculation operations. Such a method includes, for each synaptic layer, storing a plurality p of the least-significant bits of each N-bit weight w in digital memory, and storing the next n-bit portion of each weight w in an analog multiply-accumulate unit comprising an array of digital memory elements. Each digital memory element comprises n binary memory cells for storing respective bits of the n-bit portion of a weight, where n≥1 and (p+n+m)=N where m≥0 corresponds to a defined number of most-significant zero bits in weights of the synaptic layer.

Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.