Direct Gradient Calculation: Simple and Variation‐Tolerant On‐Chip Training Method for Neural Networks

Direct Gradient Calculation: Simple and Variation‐Tolerant On‐Chip Training Method for Neural Networks

On‐chip training of neural networks (NNs) is regarded as a promising training method for neuromorphic systems with analog synaptic devices. Herein, a novel on‐chip training method called direct gradient calculation (DGC) is proposed to substitute conventional backpropagation (BP). In this method, th...

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Bibliographic Details
Main Authors: Hyungyo Kim, Joon Hwang, Dongseok Kwon, Jangsaeng Kim, Min-Kyu Park, Jiseong Im, Byung-Gook Park, Jong-Ho Lee
Format: Article
Language:English
Published: Wiley 2021-08-01
Series:Advanced Intelligent Systems
Subjects:
analog synaptic devices
backpropagation
hardware-based neural networks
on-chip training
Online Access:https://doi.org/10.1002/aisy.202100064

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