Comparison of recognition accuracy of different algorithms for spectrum analysis.
<p>Comparison of recognition accuracy of different algorithms for spectrum analysis.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| مؤلفون آخرون: | , , |
| منشور في: |
2024
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| الموضوعات: | |
| الوسوم: |
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| _version_ | 1852025993513926656 |
|---|---|
| author | Yucai Wang (513301) |
| author2 | Wei Chang (442612) Jingjiao Li (4766943) Cuilei Yang (19838117) |
| author2_role | author author author |
| author_facet | Yucai Wang (513301) Wei Chang (442612) Jingjiao Li (4766943) Cuilei Yang (19838117) |
| author_role | author |
| dc.creator.none.fl_str_mv | Yucai Wang (513301) Wei Chang (442612) Jingjiao Li (4766943) Cuilei Yang (19838117) |
| dc.date.none.fl_str_mv | 2024-10-11T17:31:09Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0311897.g012 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Comparison_of_recognition_accuracy_of_different_algorithms_for_spectrum_analysis_/27213572 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Science Policy Space Science Biological Sciences not elsewhere classified wavelength division multiplexing practical application value experimental results showed bit error rate adaptive equalization algorithm enhances signal recovery enhancing railway communication achieve channel equalization speed signal processing integrating deep learning conventional wireless high dependable communication system reduce signal distortion railway communication system railway communication signal processing deep learning channel distortion equalization effect various signal modern communication effectively reduce system using xlink "> visible light transmission efficiency thereby reducing study develops softly divide reflection interference reduces interference received signals path transmission noise ratios modulation parameter interference suppression direct current |
| dc.title.none.fl_str_mv | Comparison of recognition accuracy of different algorithms for spectrum analysis. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Comparison of recognition accuracy of different algorithms for spectrum analysis.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_33d9fb7b41ab031c2c3d4dac6a14ff9e |
| identifier_str_mv | 10.1371/journal.pone.0311897.g012 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/27213572 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Comparison of recognition accuracy of different algorithms for spectrum analysis.Yucai Wang (513301)Wei Chang (442612)Jingjiao Li (4766943)Cuilei Yang (19838117)Science PolicySpace ScienceBiological Sciences not elsewhere classifiedwavelength division multiplexingpractical application valueexperimental results showedbit error rateadaptive equalization algorithmenhances signal recoveryenhancing railway communicationachieve channel equalizationspeed signal processingintegrating deep learningconventional wireless highdependable communication systemreduce signal distortionrailway communication systemrailway communicationsignal processingdeep learningchannel distortionequalization effectvarious signalmodern communicationeffectively reducesystem usingxlink ">visible lighttransmission efficiencythereby reducingstudy developssoftly dividereflection interferencereduces interferencereceived signalspath transmissionnoise ratiosmodulation parameterinterference suppressiondirect current<p>Comparison of recognition accuracy of different algorithms for spectrum analysis.</p>2024-10-11T17:31:09ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0311897.g012https://figshare.com/articles/figure/Comparison_of_recognition_accuracy_of_different_algorithms_for_spectrum_analysis_/27213572CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/272135722024-10-11T17:31:09Z |
| spellingShingle | Comparison of recognition accuracy of different algorithms for spectrum analysis. Yucai Wang (513301) Science Policy Space Science Biological Sciences not elsewhere classified wavelength division multiplexing practical application value experimental results showed bit error rate adaptive equalization algorithm enhances signal recovery enhancing railway communication achieve channel equalization speed signal processing integrating deep learning conventional wireless high dependable communication system reduce signal distortion railway communication system railway communication signal processing deep learning channel distortion equalization effect various signal modern communication effectively reduce system using xlink "> visible light transmission efficiency thereby reducing study develops softly divide reflection interference reduces interference received signals path transmission noise ratios modulation parameter interference suppression direct current |
| status_str | publishedVersion |
| title | Comparison of recognition accuracy of different algorithms for spectrum analysis. |
| title_full | Comparison of recognition accuracy of different algorithms for spectrum analysis. |
| title_fullStr | Comparison of recognition accuracy of different algorithms for spectrum analysis. |
| title_full_unstemmed | Comparison of recognition accuracy of different algorithms for spectrum analysis. |
| title_short | Comparison of recognition accuracy of different algorithms for spectrum analysis. |
| title_sort | Comparison of recognition accuracy of different algorithms for spectrum analysis. |
| topic | Science Policy Space Science Biological Sciences not elsewhere classified wavelength division multiplexing practical application value experimental results showed bit error rate adaptive equalization algorithm enhances signal recovery enhancing railway communication achieve channel equalization speed signal processing integrating deep learning conventional wireless high dependable communication system reduce signal distortion railway communication system railway communication signal processing deep learning channel distortion equalization effect various signal modern communication effectively reduce system using xlink "> visible light transmission efficiency thereby reducing study develops softly divide reflection interference reduces interference received signals path transmission noise ratios modulation parameter interference suppression direct current |