TitleAn Algorithm of Training Sample Selection for Integrated Circuit Device Modeling Based on Artificial Neural Networks
AuthorsZhang, Zhiyuan
Cui, Xiaole
Lin, Xinnan
Zhang, Lining
AffiliationPeking Univ, Shenzhen Grad Sch, ECE, Key Lab Integrated Microsyst, Shenzhen 518055, Peoples R China.
Hong Kong Univ Sci & Technol, Dept ECE, Kowloon, Hong Kong, Peoples R China.
Keywordsdevice modeling
artificial neural networks
training sample size
training accuracy
CMOS TECHNOLOGY
Issue Date2016
PublisherIEEE International Conference on Electron Devices and Solid-State Circuits (EDSSC)
CitationIEEE International Conference on Electron Devices and Solid-State Circuits (EDSSC).2016,314-317.
AbstractIn this paper, we propose a training sample selection algorithm for artificial neural networks device modeling to reduce training consuming time and data test cost. The proposed algorithm can be used to get the appropriate size of the training samples under the required training accuracy. Comparison between neural networks model and test data agrees well in a given training accuracy and proves correctness of the algorithm.
URIhttp://hdl.handle.net/20.500.11897/459779
IndexedCPCI-S(ISTP)
Appears in Collections:深圳研究生院待认领

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