Application of Multiacoustic Data in Feature Extraction of Anemometer
The acoustic characteristics of wind instruments are a major feature in the field of vocal music. This paper studies the application effect of wind power instrument feature extraction based on multiacoustic data. Combined with the acoustic data training model, the classification algorithm based on d...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/7955909 |
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| _version_ | 1832561411310485504 |
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| author | Dawei Chen Xu Guo |
| author_facet | Dawei Chen Xu Guo |
| author_sort | Dawei Chen |
| collection | DOAJ |
| description | The acoustic characteristics of wind instruments are a major feature in the field of vocal music. This paper studies the application effect of wind power instrument feature extraction based on multiacoustic data. Combined with the acoustic data training model, the classification algorithm based on deep trust network is used to process multiple acoustic data. Using multiple acoustic data for feature extraction, the recognition and matching between multiple acoustic data and wind measuring instrument are realized. The experiment not only evaluates the error of the network classification algorithm but also describes the evaluation function of the deep belief network classification algorithm in the system. The traditional SNR evaluation method is used to improve the deficiency of evaluation function. Through the deep belief network classification algorithm for self-learning, the instrument recognition method with strong applicability is established. Finally, the effectiveness of multiacoustic data in wind power instrument feature extraction is verified. |
| format | Article |
| id | doaj-art-20777a7bbfad4d20b1bbbd9c73a80e6d |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-20777a7bbfad4d20b1bbbd9c73a80e6d2025-02-03T01:25:01ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/79559097955909Application of Multiacoustic Data in Feature Extraction of AnemometerDawei Chen0Xu Guo1School of Music& Dance, Qiqihar University, Heilongjiang, Qiqihar 161000, ChinaSchool of Music& Dance, Qiqihar University, Heilongjiang, Qiqihar 161000, ChinaThe acoustic characteristics of wind instruments are a major feature in the field of vocal music. This paper studies the application effect of wind power instrument feature extraction based on multiacoustic data. Combined with the acoustic data training model, the classification algorithm based on deep trust network is used to process multiple acoustic data. Using multiple acoustic data for feature extraction, the recognition and matching between multiple acoustic data and wind measuring instrument are realized. The experiment not only evaluates the error of the network classification algorithm but also describes the evaluation function of the deep belief network classification algorithm in the system. The traditional SNR evaluation method is used to improve the deficiency of evaluation function. Through the deep belief network classification algorithm for self-learning, the instrument recognition method with strong applicability is established. Finally, the effectiveness of multiacoustic data in wind power instrument feature extraction is verified.http://dx.doi.org/10.1155/2021/7955909 |
| spellingShingle | Dawei Chen Xu Guo Application of Multiacoustic Data in Feature Extraction of Anemometer Complexity |
| title | Application of Multiacoustic Data in Feature Extraction of Anemometer |
| title_full | Application of Multiacoustic Data in Feature Extraction of Anemometer |
| title_fullStr | Application of Multiacoustic Data in Feature Extraction of Anemometer |
| title_full_unstemmed | Application of Multiacoustic Data in Feature Extraction of Anemometer |
| title_short | Application of Multiacoustic Data in Feature Extraction of Anemometer |
| title_sort | application of multiacoustic data in feature extraction of anemometer |
| url | http://dx.doi.org/10.1155/2021/7955909 |
| work_keys_str_mv | AT daweichen applicationofmultiacousticdatainfeatureextractionofanemometer AT xuguo applicationofmultiacousticdatainfeatureextractionofanemometer |