Neural network online training platform based on embedded system

WANG Jian-wei; SONG Zhi-huan

doi:10.13873/j.1000-97872010.08.040

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Neural network online training platform based on embedded system

更新时间：2025-09-11

- Neural network online training platform based on embedded system
- Vol. 29, Issue 8, Pages: 100-103(2010)
- 作者机构：
  
  浙江大学工业控制研究所工业控制技术国家重点实验室
- 作者简介：
- 基金信息：
- DOI：10.13873/j.1000-97872010.08.040
  CLC： TP183
- Published：2010
- 稿件说明：
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[1]王健伟,宋执环.基于嵌入式系统的神经网络在线训练平台实现[J].传感器与微系统,2010,29(08):100-103.

WANG Jian-wei, SONG Zhi-huan. Neural network online training platform based on embedded system[J]. 2010, 29(8): 100-103.
[1]王健伟,宋执环.基于嵌入式系统的神经网络在线训练平台实现[J].传感器与微系统,2010,29(08):100-103. DOI： 10.13873/j.1000-97872010.08.040.

WANG Jian-wei, SONG Zhi-huan. Neural network online training platform based on embedded system[J]. 2010, 29(8): 100-103. DOI： 10.13873/j.1000-97872010.08.040.

摘要

基于最新的工业应用双核处理器OMAP—L137设计了一种神经网络软测量模型在线训练平台。该平台以ARM与浮点DSP双核控制器为核心。针对神经网络隐含层节点数、训练中止条件、学习率等相关参数的确定进行了研究与测试

将优化的神经网络算法成功移植到嵌入式平台

支持神经网络软测量模型的在线训练。通过对相关数据集的测试

结果表明:系统具有高速、高精度等优良性能。

Abstract

A soft measurement model online training platform is designed based on OMAP—L137

which is a new double-core processor for industry.By analyzing the hidden-layer nodes of neural network

stop criterion of training and learning rate

the optimized neural network（NN）is realized in the double-core（ARM and floating point DSP）platform that supports on-line training of soft measurement model.The testing of datasets demonstrates the platform has excellent performance of high-precision and high-speed.

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references

软测量技术及其应用 [J]. 俞金寿. 自动化仪表 . 2008(01)

基于嵌入式系统的优化算法设计和研究 [D]. 王玉常. 浙江大学 2008

人工神经网络与模拟进化计算[M]. 清华大学出版社 , 阎平凡,张长水编著, 2005

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