{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/dctnet-and-pcanet-for-acoustic-signal-feature","title":"DCTNet and PCANet for acoustic signal feature extraction","arxiv_id":"1605.01755","date":"2016-04-28","proceeding":null,"authors":["Yin Xian","Andrew Thompson","Xiaobai Sun","Douglas Nowacek","Loren Nolte"],"abstract":"We introduce the use of DCTNet, an efficient approximation and alternative to\nPCANet, for acoustic signal classification. In PCANet, the eigenfunctions of\nthe local sample covariance matrix (PCA) are used as filterbanks for\nconvolution and feature extraction. When the eigenfunctions are well\napproximated by the Discrete Cosine Transform (DCT) functions, each layer of of\nPCANet and DCTNet is essentially a time-frequency representation. We relate\nDCTNet to spectral feature representation methods, such as the the short time\nFourier transform (STFT), spectrogram and linear frequency spectral\ncoefficients (LFSC). Experimental results on whale vocalization data show that\nDCTNet improves classification rate, demonstrating DCTNet's applicability to\nsignal processing problems such as underwater acoustics.","url_abs":"http://arxiv.org/abs/1605.01755v1","url_pdf":"http://arxiv.org/pdf/1605.01755v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"dctnet-and-pcanet-for-acoustic-signal-feature","repo_url":"https://github.com/poline3939/DCTNet","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[{"method_slug":"discrete-cosine-transform","method_name":"Discrete Cosine Transform"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}