Research on Spaceborne Neural Network Accelerator and Its Fault Tolerance Design

Research on Spaceborne Neural Network Accelerator and Its Fault Tolerance Design

To meet the high-reliability requirements of real-time on-orbit tasks, this paper proposes a fault-tolerant reinforcement design method for spaceborne intelligent processing algorithms based on convolutional neural networks (CNNs). This method is built on a CNN accelerator using Field-Programmable G...

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Bibliographic Details
Main Authors: Yingzhao Shao, Junyi Wang, Xiaodong Han, Yunsong Li, Yaolin Li, Zhanpeng Tao
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Remote Sensing
Subjects:
spaceborne computing
single-event upset
convolutional neural network
field-programmable gate array
fault-tolerant design
Online Access:https://www.mdpi.com/2072-4292/17/1/69
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