Matches in SemOpenAlex for { <https://semopenalex.org/work/W2959868599> ?p ?o ?g. }
Showing items 1 to 96 of
96
with 100 items per page.
- W2959868599 endingPage "92660" @default.
- W2959868599 startingPage "92651" @default.
- W2959868599 abstract "Unsupervised learning is applicable to classification that does not know the number of specific categories in advance, and sparse auto-encoders (SAE) are widely used for feature extraction of unsupervised learning. Therefore, this paper proposes an electromagnetic signal classification system based on SAE which is combined with the machine learning clustering algorithm. In particular, we propose to perform feature preprocessing on signals using STFT. Then, the features extracted by SAE training are clustered by t-SNE and DBSCAN to obtain clustering results. Finally, we prove the feasibility of this method classification by comparing with traditional clustering methods. Because of the feature extraction, SAE not only learns the key feature information but also effectively compresses the data content, which greatly reduces the data dimension that the clustering algorithm needs to deal with and improves the clustering accuracy. As the experimental results show, the evaluation indicators of the result obtained by our method are significantly improved compared with the traditional clustering algorithms, the compactness (CP) index decreases by 73.76%; the Davies-Bouldin Index (DB) decreases by 18.50%; the Dunn Validity Index (DVI) increases by 6.24%; and the Rand Index (RI) increases by 43.14%." @default.
- W2959868599 created "2019-07-23" @default.
- W2959868599 creator A5048075953 @default.
- W2959868599 creator A5048453574 @default.
- W2959868599 creator A5059778636 @default.
- W2959868599 creator A5068290128 @default.
- W2959868599 date "2019-01-01" @default.
- W2959868599 modified "2023-10-17" @default.
- W2959868599 title "Pulses Classification Based on Sparse Auto-Encoders Neural Networks" @default.
- W2959868599 cites W1491965087 @default.
- W2959868599 cites W1975742418 @default.
- W2959868599 cites W1986754283 @default.
- W2959868599 cites W2025768430 @default.
- W2959868599 cites W2028628242 @default.
- W2959868599 cites W2044925215 @default.
- W2959868599 cites W2074047085 @default.
- W2959868599 cites W2091467105 @default.
- W2959868599 cites W2092523626 @default.
- W2959868599 cites W2100835628 @default.
- W2959868599 cites W2102731100 @default.
- W2959868599 cites W2103868202 @default.
- W2959868599 cites W2108031918 @default.
- W2959868599 cites W2121169814 @default.
- W2959868599 cites W2123496439 @default.
- W2959868599 cites W2126326837 @default.
- W2959868599 cites W2344031149 @default.
- W2959868599 cites W2529970009 @default.
- W2959868599 cites W2553986398 @default.
- W2959868599 cites W2588862697 @default.
- W2959868599 cites W2591880439 @default.
- W2959868599 cites W2597584210 @default.
- W2959868599 cites W2621841016 @default.
- W2959868599 cites W2741139694 @default.
- W2959868599 cites W2783108935 @default.
- W2959868599 cites W2791871958 @default.
- W2959868599 cites W2796031265 @default.
- W2959868599 cites W2799007077 @default.
- W2959868599 doi "https://doi.org/10.1109/access.2019.2927724" @default.
- W2959868599 hasPublicationYear "2019" @default.
- W2959868599 type Work @default.
- W2959868599 sameAs 2959868599 @default.
- W2959868599 citedByCount "6" @default.
- W2959868599 countsByYear W29598685992021 @default.
- W2959868599 countsByYear W29598685992022 @default.
- W2959868599 countsByYear W29598685992023 @default.
- W2959868599 crossrefType "journal-article" @default.
- W2959868599 hasAuthorship W2959868599A5048075953 @default.
- W2959868599 hasAuthorship W2959868599A5048453574 @default.
- W2959868599 hasAuthorship W2959868599A5059778636 @default.
- W2959868599 hasAuthorship W2959868599A5068290128 @default.
- W2959868599 hasBestOaLocation W29598685991 @default.
- W2959868599 hasConcept C124101348 @default.
- W2959868599 hasConcept C138885662 @default.
- W2959868599 hasConcept C153180895 @default.
- W2959868599 hasConcept C154945302 @default.
- W2959868599 hasConcept C2776401178 @default.
- W2959868599 hasConcept C34736171 @default.
- W2959868599 hasConcept C41008148 @default.
- W2959868599 hasConcept C41895202 @default.
- W2959868599 hasConcept C50644808 @default.
- W2959868599 hasConcept C52622490 @default.
- W2959868599 hasConcept C73555534 @default.
- W2959868599 hasConcept C8038995 @default.
- W2959868599 hasConceptScore W2959868599C124101348 @default.
- W2959868599 hasConceptScore W2959868599C138885662 @default.
- W2959868599 hasConceptScore W2959868599C153180895 @default.
- W2959868599 hasConceptScore W2959868599C154945302 @default.
- W2959868599 hasConceptScore W2959868599C2776401178 @default.
- W2959868599 hasConceptScore W2959868599C34736171 @default.
- W2959868599 hasConceptScore W2959868599C41008148 @default.
- W2959868599 hasConceptScore W2959868599C41895202 @default.
- W2959868599 hasConceptScore W2959868599C50644808 @default.
- W2959868599 hasConceptScore W2959868599C52622490 @default.
- W2959868599 hasConceptScore W2959868599C73555534 @default.
- W2959868599 hasConceptScore W2959868599C8038995 @default.
- W2959868599 hasFunder F4320321001 @default.
- W2959868599 hasLocation W29598685991 @default.
- W2959868599 hasOpenAccess W2959868599 @default.
- W2959868599 hasPrimaryLocation W29598685991 @default.
- W2959868599 hasRelatedWork W1629127207 @default.
- W2959868599 hasRelatedWork W2066827917 @default.
- W2959868599 hasRelatedWork W206706326 @default.
- W2959868599 hasRelatedWork W2095030957 @default.
- W2959868599 hasRelatedWork W2132641928 @default.
- W2959868599 hasRelatedWork W2397288865 @default.
- W2959868599 hasRelatedWork W2804364458 @default.
- W2959868599 hasRelatedWork W2884201223 @default.
- W2959868599 hasRelatedWork W4298130764 @default.
- W2959868599 hasRelatedWork W4310225030 @default.
- W2959868599 hasVolume "7" @default.
- W2959868599 isParatext "false" @default.
- W2959868599 isRetracted "false" @default.
- W2959868599 magId "2959868599" @default.
- W2959868599 workType "article" @default.