{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,2]],"date-time":"2026-01-02T07:47:27Z","timestamp":1767340047449,"version":"3.40.3"},"publisher-location":"Cham","reference-count":17,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030736705"},{"type":"electronic","value":"9783030736712"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-73671-2_13","type":"book-chapter","created":{"date-parts":[[2021,7,6]],"date-time":"2021-07-06T11:12:10Z","timestamp":1625569930000},"page":"132-143","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["The Blind Separation of Cockpit Mixed Signals Based on Fast Independent Component Analysis"],"prefix":"10.1007","author":[{"given":"Zhengmao","family":"Wu","sequence":"first","affiliation":[]},{"given":"Sihai","family":"Li","sequence":"additional","affiliation":[]},{"given":"Jing","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Mingrui","family":"Chen","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,7,7]]},"reference":[{"key":"13_CR1","volume-title":"Advisory Circular AC20-186","author":"Federal Aviation Administration","year":"2016","unstructured":"Federal Aviation Administration: Advisory Circular AC20-186. FAA, Washington, D.C. (2016)"},{"key":"13_CR2","unstructured":"National Transportation Safety Board: Safety Recommendation Report: Extended Duration Cockpit Voice Recorders. ASR-18\u201304. NTSB, Washington (2018)"},{"key":"13_CR3","unstructured":"European Union: Commission Regulation (EU) 2015\/2338: Official Journal of the European Union, L 330, 16 December 2015, pp. 1\u201311 (2015)"},{"issue":"6","key":"13_CR4","doi-asserted-by":"publisher","first-page":"320","DOI":"10.4103\/0256-4602.45424","volume":"5","author":"DP Acharya","year":"2014","unstructured":"Acharya, D.P., Panda, G.: A review of independent component analysis techniques and their applications. IETE Tech. Rev. 5(6), 320\u2013332 (2014)","journal-title":"IETE Tech. Rev."},{"key":"13_CR5","doi-asserted-by":"crossref","unstructured":"Nikam, S., Deosarkar, S.: Fast ICA based technique for non-invasive fetal ECG extraction. In: 2016 Conference on Advances in Signal Processing (CASP), pp. 60\u201365 (2016)","DOI":"10.1109\/CASP.2016.7746138"},{"key":"13_CR6","unstructured":"SHOGUN-TOOLBOX Homepage. http:\/\/www.shogun-toolbox.org. Accessed 18 Oct 2020"},{"key":"13_CR7","doi-asserted-by":"publisher","first-page":"4","DOI":"10.3389\/fncom.2019.00004","volume":"13","author":"A D\u2019Angiulli","year":"2019","unstructured":"D\u2019Angiulli, A., Devenyi, P.: Retooling computational techniques for EEG-based neurocognitive modeling of children\u2019s data, validity and prospects for learning and education. Front. Comput. Neurosci. 13, 4 (2019)","journal-title":"Front. Comput. Neurosci."},{"issue":"2","key":"13_CR8","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1109\/TASLP.2018.2877894","volume":"27","author":"X Feifei","year":"2019","unstructured":"Feifei, X., Stefan, G., Birger, K., et al.: Joint estimation of reverberation time and early-to-late reverberation ratio from single-channel speech signals. IEEE\/ACM Trans. Audio Speech Lang. Process. (TASLP) 27(2), 255\u2013267 (2019)","journal-title":"IEEE\/ACM Trans. Audio Speech Lang. Process. (TASLP)"},{"issue":"7","key":"13_CR9","doi-asserted-by":"publisher","first-page":"2593","DOI":"10.3390\/app10072593","volume":"10","author":"K Zhang","year":"2020","unstructured":"Zhang, K., Wei, Y., Wu, D., Wang, Y.: Adaptive speech separation based on beamforming and frequency domain-independent component analysis. Appl. Sci. 10(7), 2593 (2020)","journal-title":"Appl. Sci."},{"issue":"1","key":"13_CR10","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1007\/s10772-019-09595-9","volume":"22","author":"K Mohanaprasad","year":"2019","unstructured":"Mohanaprasad, K., Singh, A., Sinha, K., Ketkar, T.: Noise reduction in speech signals using adaptive independent component analysis (ICA) for hands free communication devices. Int. J. Speech Technol. 22(1), 169\u2013177 (2019). https:\/\/doi.org\/10.1007\/s10772-019-09595-9","journal-title":"Int. J. Speech Technol."},{"key":"13_CR11","doi-asserted-by":"crossref","unstructured":"Karrupusamy, P., et al. (eds.): Speech separation using deep learning. In: ICSCN 2019, LNDECT 39, pp. 319\u2013326 (2020)","DOI":"10.1007\/978-3-030-34515-0_34"},{"issue":"3","key":"13_CR12","doi-asserted-by":"publisher","first-page":"1","DOI":"10.4018\/IJAPUC.2016070101","volume":"8","author":"T Gao","year":"2016","unstructured":"Gao, T., Li, J.: The research and simulation of blind source separation algorithm. Int. J. Adv. Pervasive Ubiquitous Comput. (IJAPUC) 8(3), 1\u201336 (2016)","journal-title":"Int. J. Adv. Pervasive Ubiquitous Comput. (IJAPUC)"},{"key":"13_CR13","doi-asserted-by":"publisher","first-page":"363","DOI":"10.1016\/j.procs.2018.07.270","volume":"126","author":"N Hassan","year":"2018","unstructured":"Hassan, N., Ramli, D.A.: A comparative study of blind source separation for bioacoustics sounds based on FastICA PCA and NMF. Procedia Comput. Sci. 126, 363\u2013372 (2018)","journal-title":"Procedia Comput. Sci."},{"issue":"4","key":"13_CR14","doi-asserted-by":"publisher","first-page":"693","DOI":"10.1049\/iet-its.2018.5094","volume":"13","author":"P Lei","year":"2019","unstructured":"Lei, P., Chen, M., Wang, J.: Speech enhancement for in-vehicle voice control systems using wavelet analysis and blind source separation. IET Intel. Transp. Syst. 13(4), 693\u2013702 (2019)","journal-title":"IET Intel. Transp. Syst."},{"issue":"6","key":"13_CR15","first-page":"364","volume":"6","author":"TVP Sundararajan","year":"2016","unstructured":"Sundararajan, T.V.P., Sampath, P., Kiruthika, T., Dharani, E.: Separation of different voices in speech using fast Ica algorithm. Int. J. Eng. Manag. Res. (IJEMR) 6(6), 364\u2013368 (2016)","journal-title":"Int. J. Eng. Manag. Res. (IJEMR)"},{"issue":"3","key":"13_CR16","doi-asserted-by":"publisher","first-page":"348","DOI":"10.3102\/1076998619832248","volume":"44","author":"J Hao","year":"2019","unstructured":"Hao, J., Ho, T.K.: Machine learning made easy: a review of scikit-learn package in python programming language. J. Educ. Behav. Stat. 44(3), 348\u2013361 (2019)","journal-title":"J. Educ. Behav. Stat."},{"key":"13_CR17","unstructured":"GITHUT Homepage. https:\/\/github.com\/LiangjunFeng\/Machine-Learning\/blob\/master\/9.FastICA.py. Accessed 21 Oct 2020"}],"container-title":["Lecture Notes in Computer Science","Cyberspace Safety and Security"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-73671-2_13","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,7,6]],"date-time":"2021-07-06T11:19:39Z","timestamp":1625570379000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-73671-2_13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030736705","9783030736712"],"references-count":17,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-73671-2_13","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"7 July 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"CSS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Symposium on Cyberspace Safety and Security","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Haikou","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2020","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"1 December 2020","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 December 2020","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"css2020","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.hainanu.edu.cn\/scscs\/css2020\/index.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"82","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"46% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}