The individual identification method of wireless device based on dimensionality reduction and machine learning-Reference-Cited by-同舟云学术

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The individual identification method of wireless device based on dimensionality reduction and machine learning

Published:2017-12-15 Issue:6 Volume:75 Page:3010-3027
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Lin Yun,Zhu Xiaolei,Zheng Zhigao^ORCID,Dou Zheng,Zhou Ruolin

Funder

National Natural Science Foundation of China

Key Development Program of Basic Research of China

Fundamental Research Funds for the Central Universities

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

http://link.springer.com/content/pdf/10.1007/s11227-017-2216-2.pdf

Reference52 articles.

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3. Breiman L (2001) Random forests. Mach Learn 45(1):5–32

4. Campbell-Washburn AE, Atkinson D, Nagy Z, Chan RW, Josephs O, Lythgoe MF, Ordidge RJ, Thomas DL (2016) Using the robust principal component analysis algorithm to remove rf spike artifacts from mr images. Magn Reson Med 75(6):2517–2525

5. Candès EJ, Li X, Ma Y, Wright J (2011) Robust principal component analysis? J ACM 58(3):11

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