Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification
Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency,...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sun, Na [verfasserIn] Zhou, Yajian [verfasserIn] Yang, Yixian [verfasserIn] |
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| Format: |
E-Artikel |
|---|---|
| Sprache: |
Englisch |
| Erschienen: |
2010 |
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| Schlagwörter: |
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| Übergeordnetes Werk: |
Enthalten in: Frontiers of electrical and electronic engineering in China - Berlin : Heidelberg : Springer, 2006, 5(2010), 4 vom: 21. Juli, Seite 488-492 |
|---|---|
| Übergeordnetes Werk: |
volume:5 ; year:2010 ; number:4 ; day:21 ; month:07 ; pages:488-492 |
| Links: |
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| DOI / URN: |
10.1007/s11460-010-0094-y |
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SPR019849559 |
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| 520 | |a Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved. | ||
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10.1007/s11460-010-0094-y doi (DE-627)SPR019849559 (SPR)s11460-010-0094-y-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Sun, Na verfasserin aut Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved. polyspectral kernel (dpeaa)DE-He213 support vector machine (SVM) (dpeaa)DE-He213 neighborhood rough set (dpeaa)DE-He213 weighted feature set (dpeaa)DE-He213 weighted kernel (dpeaa)DE-He213 Zhou, Yajian verfasserin aut Yang, Yixian verfasserin aut Enthalten in Frontiers of electrical and electronic engineering in China Berlin : Heidelberg : Springer, 2006 5(2010), 4 vom: 21. Juli, Seite 488-492 (DE-627)510464297 (DE-600)2230606-7 1673-3584 nnns volume:5 year:2010 number:4 day:21 month:07 pages:488-492 https://dx.doi.org/10.1007/s11460-010-0094-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2190 53.00 ASE AR 5 2010 4 21 07 488-492 |
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10.1007/s11460-010-0094-y doi (DE-627)SPR019849559 (SPR)s11460-010-0094-y-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Sun, Na verfasserin aut Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved. polyspectral kernel (dpeaa)DE-He213 support vector machine (SVM) (dpeaa)DE-He213 neighborhood rough set (dpeaa)DE-He213 weighted feature set (dpeaa)DE-He213 weighted kernel (dpeaa)DE-He213 Zhou, Yajian verfasserin aut Yang, Yixian verfasserin aut Enthalten in Frontiers of electrical and electronic engineering in China Berlin : Heidelberg : Springer, 2006 5(2010), 4 vom: 21. Juli, Seite 488-492 (DE-627)510464297 (DE-600)2230606-7 1673-3584 nnns volume:5 year:2010 number:4 day:21 month:07 pages:488-492 https://dx.doi.org/10.1007/s11460-010-0094-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2190 53.00 ASE AR 5 2010 4 21 07 488-492 |
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10.1007/s11460-010-0094-y doi (DE-627)SPR019849559 (SPR)s11460-010-0094-y-e DE-627 ger DE-627 rakwb eng 620 ASE 53.00 bkl Sun, Na verfasserin aut Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved. polyspectral kernel (dpeaa)DE-He213 support vector machine (SVM) (dpeaa)DE-He213 neighborhood rough set (dpeaa)DE-He213 weighted feature set (dpeaa)DE-He213 weighted kernel (dpeaa)DE-He213 Zhou, Yajian verfasserin aut Yang, Yixian verfasserin aut Enthalten in Frontiers of electrical and electronic engineering in China Berlin : Heidelberg : Springer, 2006 5(2010), 4 vom: 21. Juli, Seite 488-492 (DE-627)510464297 (DE-600)2230606-7 1673-3584 nnns volume:5 year:2010 number:4 day:21 month:07 pages:488-492 https://dx.doi.org/10.1007/s11460-010-0094-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_20 GBV_ILN_40 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_110 GBV_ILN_120 GBV_ILN_161 GBV_ILN_293 GBV_ILN_702 GBV_ILN_2005 GBV_ILN_2014 GBV_ILN_2018 GBV_ILN_2190 53.00 ASE AR 5 2010 4 21 07 488-492 |
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Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification |
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Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved. |
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Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved. |
| abstract_unstemmed |
Abstract This paper presents a method using support vector machine with polyspectral kernels for classification of individual transmitters. Then, the neighborhood-rough-set-based weighted feature set is proposed. The experiments of the algorithms mentioned above indicate that they have consistency, which raises a new weighted kernel. The experiment shows that better classification rate can be achieved. |
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| title_short |
Consistency of weighted feature set and polyspectral kernels in individual communication transmitter identification |
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https://dx.doi.org/10.1007/s11460-010-0094-y |
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Zhou, Yajian Yang, Yixian |
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10.1007/s11460-010-0094-y |
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