Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters

Xin Xu; Wei Wang; Jiaheng Lu; Jin Chen

doi:10.1007/978-3-319-25159-2_56

Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters

Xin Xu, Wei Wang, Jiaheng Lu, Jin Chen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

In the age of big data, the emitter parameter measurement data is generally characteristic of uncertainty in the form of normallydistributed intervals, enormous size and continuous growth. However, existing interval-valued data analysis methods generally assume a uniform distribution instead and are unable to adapt to the rapid growth of volume. To address the above problems, we have brought forward an incremental distributed weighted class discriminant analysis method on interval-valued emitter parameters. Extensive experiments indicate that our method is able to cope with these new characteristics effectively.

Original language	English
Title of host publication	Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings
Editors	Zili Zhang, Songmao Zhang, Zili Zhang, Martin Wirsing, Martin Wirsing, Martin Wirsing, Zili Zhang, Songmao Zhang, Songmao Zhang
Pages	619-624
Number of pages	6
DOIs	https://doi.org/10.1007/978-3-319-25159-2_56
State	Published - 2015
Event	8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 - Chongqing, China Duration: Oct 28 2015 → Oct 30 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9403
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015
Country/Territory	China
City	Chongqing
Period	10/28/15 → 10/30/15

Bibliographical note

Funding Information:
This work was supported by National Natural Science Foundation of China (No. 61402426, 61373129) and Chemical Sciences, Geosciences and Biosciences Division, Office of Basic Energy Sciences, Office of Science, U.S. Department of Energy (No. DEFG02-91ER20021) and partially supported by Collaborative Innovation Center of Novel Software Technology and Industrialization.

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

Keywords

Class discriminant analysis
Distributed computing
Emitter identification
Fuzzy pattern mining
Incremental learning
Signal processing

ASJC Scopus subject areas

Theoretical Computer Science
Computer Science (all)

Access to Document

10.1007/978-3-319-25159-2_56

Cite this

Xu, X., Wang, W., Lu, J., & Chen, J. (2015). Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters. In Z. Zhang, S. Zhang, Z. Zhang, M. Wirsing, M. Wirsing, M. Wirsing, Z. Zhang, S. Zhang, & S. Zhang (Eds.), Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings (pp. 619-624). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9403). https://doi.org/10.1007/978-3-319-25159-2_56

Xu, Xin ; Wang, Wei ; Lu, Jiaheng et al. / Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters. Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. editor / Zili Zhang ; Songmao Zhang ; Zili Zhang ; Martin Wirsing ; Martin Wirsing ; Martin Wirsing ; Zili Zhang ; Songmao Zhang ; Songmao Zhang. 2015. pp. 619-624 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{f1f04b693833465b941fc3ea524ccab3,

title = "Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters",

abstract = "In the age of big data, the emitter parameter measurement data is generally characteristic of uncertainty in the form of normallydistributed intervals, enormous size and continuous growth. However, existing interval-valued data analysis methods generally assume a uniform distribution instead and are unable to adapt to the rapid growth of volume. To address the above problems, we have brought forward an incremental distributed weighted class discriminant analysis method on interval-valued emitter parameters. Extensive experiments indicate that our method is able to cope with these new characteristics effectively.",

keywords = "Class discriminant analysis, Distributed computing, Emitter identification, Fuzzy pattern mining, Incremental learning, Signal processing",

author = "Xin Xu and Wei Wang and Jiaheng Lu and Jin Chen",

note = "Funding Information: This work was supported by National Natural Science Foundation of China (No. 61402426, 61373129) and Chemical Sciences, Geosciences and Biosciences Division, Office of Basic Energy Sciences, Office of Science, U.S. Department of Energy (No. DEFG02-91ER20021) and partially supported by Collaborative Innovation Center of Novel Software Technology and Industrialization. Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015 ; Conference date: 28-10-2015 Through 30-10-2015",

year = "2015",

doi = "10.1007/978-3-319-25159-2_56",

language = "English",

isbn = "9783319251585",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

pages = "619--624",

editor = "Zili Zhang and Songmao Zhang and Zili Zhang and Martin Wirsing and Martin Wirsing and Martin Wirsing and Zili Zhang and Songmao Zhang and Songmao Zhang",

booktitle = "Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings",

}

Xu, X, Wang, W, Lu, J & Chen, J 2015, Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters. in Z Zhang, S Zhang, Z Zhang, M Wirsing, M Wirsing, M Wirsing, Z Zhang, S Zhang & S Zhang (eds), Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9403, pp. 619-624, 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015, Chongqing, China, 10/28/15. https://doi.org/10.1007/978-3-319-25159-2_56

Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters. / Xu, Xin; Wang, Wei; Lu, Jiaheng et al.
Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. ed. / Zili Zhang; Songmao Zhang; Zili Zhang; Martin Wirsing; Martin Wirsing; Martin Wirsing; Zili Zhang; Songmao Zhang; Songmao Zhang. 2015. p. 619-624 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9403).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters

AU - Xu, Xin

AU - Wang, Wei

AU - Lu, Jiaheng

AU - Chen, Jin

N1 - Funding Information: This work was supported by National Natural Science Foundation of China (No. 61402426, 61373129) and Chemical Sciences, Geosciences and Biosciences Division, Office of Basic Energy Sciences, Office of Science, U.S. Department of Energy (No. DEFG02-91ER20021) and partially supported by Collaborative Innovation Center of Novel Software Technology and Industrialization. Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - In the age of big data, the emitter parameter measurement data is generally characteristic of uncertainty in the form of normallydistributed intervals, enormous size and continuous growth. However, existing interval-valued data analysis methods generally assume a uniform distribution instead and are unable to adapt to the rapid growth of volume. To address the above problems, we have brought forward an incremental distributed weighted class discriminant analysis method on interval-valued emitter parameters. Extensive experiments indicate that our method is able to cope with these new characteristics effectively.

AB - In the age of big data, the emitter parameter measurement data is generally characteristic of uncertainty in the form of normallydistributed intervals, enormous size and continuous growth. However, existing interval-valued data analysis methods generally assume a uniform distribution instead and are unable to adapt to the rapid growth of volume. To address the above problems, we have brought forward an incremental distributed weighted class discriminant analysis method on interval-valued emitter parameters. Extensive experiments indicate that our method is able to cope with these new characteristics effectively.

KW - Class discriminant analysis

KW - Distributed computing

KW - Emitter identification

KW - Fuzzy pattern mining

KW - Incremental learning

KW - Signal processing

UR - http://www.scopus.com/inward/record.url?scp=84951855450&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84951855450&partnerID=8YFLogxK

U2 - 10.1007/978-3-319-25159-2_56

DO - 10.1007/978-3-319-25159-2_56

M3 - Conference contribution

AN - SCOPUS:84951855450

SN - 9783319251585

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 619

EP - 624

BT - Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings

A2 - Zhang, Zili

A2 - Zhang, Songmao

A2 - Zhang, Zili

A2 - Wirsing, Martin

A2 - Zhang, Zili

A2 - Zhang, Songmao

T2 - 8th International Conference on Knowledge Science, Engineering and Management, KSEM 2015

Y2 - 28 October 2015 through 30 October 2015

ER -

Xu X, Wang W, Lu J, Chen J. Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters. In Zhang Z, Zhang S, Zhang Z, Wirsing M, Wirsing M, Wirsing M, Zhang Z, Zhang S, Zhang S, editors, Knowledge Science, Engineering and Management - 8th International Conference, KSEM 2015, Proceedings. 2015. p. 619-624. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-25159-2_56

Incremental distributed weighted class discriminant analysis on interval-valued emitter parameters

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this