{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T22:49:39Z","timestamp":1771454979542,"version":"3.50.1"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T00:00:00Z","timestamp":1736380800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Circuits Syst Signal Process"],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1007\/s00034-024-02973-y","type":"journal-article","created":{"date-parts":[[2025,1,9]],"date-time":"2025-01-09T13:49:35Z","timestamp":1736430575000},"page":"3466-3489","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Efficiently Designed Hammerstein Spline Adaptive Filter for Ocular Noise Extraction from EEG Signals"],"prefix":"10.1007","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8759-7214","authenticated-orcid":false,"given":"Shubham","family":"Yadav","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Suman Kumar","family":"Saha","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajib","family":"Kar","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,9]]},"reference":[{"issue":"1","key":"2973_CR1","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1016\/j.dsp.2013.10.019","volume":"25","author":"MK Ahirwal","year":"2014","unstructured":"M.K. Ahirwal, A. Kumar, G.K. Singh, Adaptive filtering of EEG\/ ERP through bounded range artificial bee colony (BR-ABC) algorithm. Digital Signal Process 25(1), 164\u2013172 (2014). https:\/\/doi.org\/10.1016\/j.dsp.2013.10.019","journal-title":"Digital Signal Process"},{"issue":"6","key":"2973_CR2","doi-asserted-by":"publisher","first-page":"1491","DOI":"10.1109\/TCBB.2013.119","volume":"10","author":"MK Ahirwal","year":"2013","unstructured":"M.K. Ahirwal, A. Kumar, G.K. Singh, EEG\/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms. IEEE ACM Trans. Comput. Biol. Bioinf. 10(6), 1491\u20131504 (2013). https:\/\/doi.org\/10.1109\/TCBB.2013.119","journal-title":"IEEE ACM Trans. Comput. Biol. Bioinf."},{"key":"2973_CR3","doi-asserted-by":"publisher","first-page":"7943","DOI":"10.1007\/s00521-021-06757-2","volume":"35","author":"ZAA Alyasseri","year":"2022","unstructured":"Z.A.A. Alyasseri, A.T. Khader, M.A. Al-Betar, X.S. Yang, M.A. Mohammed, K.H. Abdulkareem, S. Kadry, I. Razzak, Multi-objective flower pollination algorithm: a new technique for EEG signal denoising. Neural Comput. Appl. 35, 7943\u20137962 (2022). https:\/\/doi.org\/10.1007\/s00521-021-06757-2","journal-title":"Neural Comput. Appl."},{"key":"2973_CR4","unstructured":"B. Azzerboni, F. L. Foresta, N. Mammone, F.C. Morabito A new approach based on Wavelet-ICA algorithms for fetal electrocardiogram extraction. In: Proc. European Symposium on Artificial Neural Networks, 193\u2013198 (2005)."},{"issue":"11","key":"2973_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/etep.2405","volume":"27","author":"K Cai","year":"2017","unstructured":"K. Cai, Z. Wang, G. Li, D. He, J. Song, Harmonic separation from grid voltage using ensemble empirical mode decomposition and independent component analysis. Int. Trans. Electr. Energy Syst. 27(11), 1\u201312 (2017). https:\/\/doi.org\/10.1002\/etep.2405","journal-title":"Int. Trans. Electr. Energy Syst."},{"issue":"8","key":"2973_CR6","doi-asserted-by":"publisher","first-page":"1819","DOI":"10.1016\/j.sigpro.2007.01.011","volume":"87","author":"ME Davies","year":"2007","unstructured":"M.E. Davies, C.J. James, Source separation using single-channel ICA. Signal Process. 87(8), 1819\u20131832 (2007). https:\/\/doi.org\/10.1016\/j.sigpro.2007.01.011","journal-title":"Signal Process."},{"issue":"3","key":"2973_CR7","doi-asserted-by":"publisher","first-page":"480","DOI":"10.1016\/j.clinph.2006.10.019","volume":"118","author":"M Fatourechi","year":"2007","unstructured":"M. Fatourechi, A. Bashashati, R.K. Ward, G.E. Birch, EMG and EOG artifacts in brain-computer interface systems: a survey. Clin. Neurophysiol. 118(3), 480\u2013494 (2007). https:\/\/doi.org\/10.1016\/j.clinph.2006.10.019","journal-title":"Clin. Neurophysiol."},{"key":"2973_CR8","doi-asserted-by":"publisher","first-page":"404","DOI":"10.1007\/s00034-016-0293-8","volume":"36","author":"HK Garg","year":"2017","unstructured":"H.K. Garg, A.K. Kohli, Excision of ocular artifacts from EEG using NVFF-RLS adaptive algorithm. Circuits Syst Signal Process 36, 404\u2013419 (2017). https:\/\/doi.org\/10.1007\/s00034-016-0293-8","journal-title":"Circuits Syst Signal Process"},{"issue":"23","key":"2973_CR9","doi-asserted-by":"publisher","first-page":"e215","DOI":"10.1161\/01.CIR.101.23.e215","volume":"101","author":"AL Goldberger","year":"2000","unstructured":"A.L. Goldberger, L.A.N. Amaral, L. Glass, J.M. Hausdorff, P.C.H. Ivanov, R.G. Mark, J.E. Mietus, G.B. Moody, C.-K. Peng, H.E. Stanley, PhysioToolkit, and PhysioNet: components of a new research resource for complex physiologic signals. Circulation 101(23), e215\u2013e220 (2000)","journal-title":"Circulation"},{"key":"2973_CR10","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/j.pisc.2016.03.002","volume":"8","author":"S Goyal","year":"2016","unstructured":"S. Goyal, S. Goswamy, A. Negi, A. Tomar, A.R. Verma, Y. Singh, Design of ANC filter using modified cuckoo search technique for ECG signal enhancement. Perspect. Sci. 8, 43\u201345 (2016). https:\/\/doi.org\/10.1016\/j.pisc.2016.03.002","journal-title":"Perspect. Sci."},{"issue":"2","key":"2973_CR11","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1049\/iet-spr.2010.0135","volume":"6","author":"C Guerrero-Mosquera","year":"2012","unstructured":"C. Guerrero-Mosquera, A. Navia-V\u00e1zquez, Automatic removal of ocular artefacts using adaptive filtering and independent component analysis for electroencephalogram data. IET Signal Process. 6(2), 99\u2013106 (2012). https:\/\/doi.org\/10.1049\/iet-spr.2010.0135","journal-title":"IET Signal Process."},{"issue":"5","key":"2973_CR12","doi-asserted-by":"publisher","first-page":"2317","DOI":"10.1007\/s00034-013-9556-9","volume":"32","author":"Y Guo","year":"2013","unstructured":"Y. Guo, S. Huang, Y. Li, G.R. Naik, Edge effect elimination in single-mixture blind source separation. Circuits Syst Signal Process. 32(5), 2317\u20132334 (2013). https:\/\/doi.org\/10.1007\/s00034-013-9556-9","journal-title":"Circuits Syst Signal Process."},{"key":"2973_CR13","doi-asserted-by":"publisher","unstructured":"Y. Guo, G.R. Naik, H. Nguyen Single channel blind source separation based local mean decomposition for biomedical applications. In: Proc. Annu. Int. Conf. IEEE EMBS, Osaka, Japan, 3\u20137 (2013). https:\/\/doi.org\/10.1109\/EMBC.2013.6611121","DOI":"10.1109\/EMBC.2013.6611121"},{"issue":"4","key":"2973_CR14","doi-asserted-by":"publisher","first-page":"175","DOI":"10.1046\/j.1440-1819.1999.00527.x","volume":"53","author":"Y Ichimaru","year":"1999","unstructured":"Y. Ichimaru, G.B. Moody, Development of the polysomnographic database on CD-ROM. Psychiatry Clin. Neurosci. 53(4), 175\u2013177 (1999)","journal-title":"Psychiatry Clin. Neurosci."},{"key":"2973_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.aeue.2022.154218","volume":"151","author":"L Janjanam","year":"2022","unstructured":"L. Janjanam, S.K. Saha, R. Kar, D. Mandal, Hammerstein-Wiener nonlinear system identification by using honey badger algorithm hybridised Sage-Husa adaptive Kalman filter with real-time applications. AEU-Int. J. Electron. C. 151, 154218 (2022). https:\/\/doi.org\/10.1016\/j.aeue.2022.154218","journal-title":"AEU-Int. J. Electron. C."},{"issue":"8","key":"2973_CR16","doi-asserted-by":"publisher","first-page":"8457","DOI":"10.1109\/TIE.2022.3213886","volume":"70","author":"L Janjanam","year":"2022","unstructured":"L. Janjanam, S.K. Saha, R. Kar, Optimal design of Hammerstein cubic spline filter for nonlinear system modelling based on snake optimiser. IEEE Trans. Industr. Electron. 70(8), 8457\u20138467 (2022). https:\/\/doi.org\/10.1109\/TIE.2022.3213886","journal-title":"IEEE Trans. Industr. Electron."},{"issue":"2","key":"2973_CR17","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1111\/1469-8986.3720163","volume":"37","author":"TP Jung","year":"2000","unstructured":"T.P. Jung, S. Makeig, S. Humphries, T.W. Lee, M.J. McKeown, V. Iragui, T.J. Sejnowski, Removing electroencephalographic artifacts by blind source separation. Psychophysiology 37(2), 163\u2013178 (2000). https:\/\/doi.org\/10.1111\/1469-8986.3720163","journal-title":"Psychophysiology"},{"issue":"5","key":"2973_CR18","doi-asserted-by":"publisher","first-page":"251","DOI":"10.2299\/jsp.18.251","volume":"18","author":"S Kanoga","year":"2014","unstructured":"S. Kanoga, Y. Mitsukura, Eye-blink artifact reduction using 2-step non-negative matrix factorisation for single-channel electroencephalographic signals. J. Signal Process. 18(5), 251\u2013257 (2014). https:\/\/doi.org\/10.2299\/jsp.18.251","journal-title":"J. Signal Process."},{"key":"2973_CR19","doi-asserted-by":"publisher","first-page":"300","DOI":"10.1016\/j.future.2020.03.055","volume":"111","author":"S Li","year":"2020","unstructured":"S. Li, H. Chen, M. Wang, A.A. Heidari, S. Mirjalili, Slime mould algorithm: a new method for stochastic optimization. Futur. Gener. Comput. Syst. 111, 300\u2013323 (2020). https:\/\/doi.org\/10.1016\/j.future.2020.03.055","journal-title":"Futur. Gener. Comput. Syst."},{"issue":"6","key":"2973_CR20","doi-asserted-by":"publisher","first-page":"421","DOI":"10.1016\/j.ndteint.2004.11.005","volume":"38","author":"J Lin","year":"2005","unstructured":"J. Lin, A. Zhang, Fault feature separation using wavelet-ICA filter. NDT and E Int. 38(6), 421\u2013427 (2005). https:\/\/doi.org\/10.1016\/j.ndteint.2004.11.005","journal-title":"NDT and E Int."},{"key":"2973_CR21","doi-asserted-by":"publisher","first-page":"8279","DOI":"10.1109\/JSEN.2016.2560219","volume":"16","author":"AK Maddirala","year":"2016","unstructured":"A.K. Maddirala, R.A. Shaik, Removal of EOG artifacts from single-channel EEG signals using combined singular spectrum analysis and adaptive noise canceler. IEEE Sens. J. 16, 8279\u20138287 (2016). https:\/\/doi.org\/10.1109\/JSEN.2016.2560219","journal-title":"IEEE Sens. J."},{"issue":"2","key":"2973_CR22","doi-asserted-by":"publisher","first-page":"382","DOI":"10.1109\/TIM.2017.2775358","volume":"67","author":"AK Maddirala","year":"2018","unstructured":"A.K. Maddirala, R.A. Shaik, Separation of sources from single-channel EEG signals using independent component analysis. IEEE Trans. Instrum. Meas. 67(2), 382\u2013393 (2018). https:\/\/doi.org\/10.1109\/TIM.2017.2775358","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"9","key":"2973_CR23","doi-asserted-by":"publisher","first-page":"2188","DOI":"10.1109\/TBME.2010.2051440","volume":"57","author":"B Mijovic","year":"2010","unstructured":"B. Mijovic, M.D. Vos, I. Gligorijevic, J. Taelman, S. Van Huffel, Source separation from single-channel recordings by combining empirical-mode decomposition and independent component analysis. IEEE Trans. Biomed. Eng. 57(9), 2188\u20132196 (2010). https:\/\/doi.org\/10.1109\/TBME.2010.2051440","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"3","key":"2973_CR24","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1088\/1741-2560\/3\/3\/003","volume":"3","author":"M Naeem","year":"2006","unstructured":"M. Naeem, C. Brunner, R. Leeb, B. Graimann, G. Pfurtscheller, Separability of four-class motor imagery data using independent components analysis. J. Neural Eng. 3(3), 208\u2013216 (2006). https:\/\/doi.org\/10.1088\/1741-2560\/3\/3\/003","journal-title":"J. Neural Eng."},{"issue":"4","key":"2973_CR25","doi-asserted-by":"publisher","first-page":"682","DOI":"10.1109\/TBCAS.2019.2916676","volume":"13","author":"C Nayak","year":"2019","unstructured":"C. Nayak, S.K. Saha, R. Kar, D. Mandal, An efficient and robust digital fractional-order differentiator-based ECG pre-processor design for QRS detection. IEEE Trans. Biomed. Circuits Syst. 13(4), 682\u2013696 (2019). https:\/\/doi.org\/10.1109\/TBCAS.2019.2916676","journal-title":"IEEE Trans. Biomed. Circuits Syst."},{"key":"2973_CR26","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2020.101987","volume":"60","author":"SK Noorbasha","year":"2020","unstructured":"S.K. Noorbasha, G.F. Sudha, Removal of EOG artifacts from single channel EEG: an efficient model combining overlap segmented ASSA and ANC. Biomed. Signal Process. Control 60, 101987 (2020). https:\/\/doi.org\/10.1016\/j.bspc.2020.101987","journal-title":"Biomed. Signal Process. Control"},{"key":"2973_CR27","doi-asserted-by":"publisher","first-page":"102168","DOI":"10.1016\/j.bspc.2020.102168","volume":"63","author":"SK Noorbasha","year":"2021","unstructured":"S.K. Noorbasha, G.F. Sudha, Removal of EOG artifacts and separation of different cerebral activity components from single-channel EEG-An efficient approach combining SSA\u2013ICA with wavelet thresholding for BCI applications. Biomed. Signal Process. Control 63, 102168 (2021). https:\/\/doi.org\/10.1016\/j.bspc.2020.102168","journal-title":"Biomed. Signal Process. Control"},{"key":"2973_CR28","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1016\/j.matcom.2022.02.030","volume":"198","author":"BN \u00d6rneka","year":"2022","unstructured":"B.N. \u00d6rneka, S.B. Aydemira, T. D\u00fczenlib, B.L. \u00d6zaka, A novel version of slime mould algorithm for global optimization and real-world engineering problems enhanced slime mould algorithm. Math. Comput. Simul 198, 253\u2013288 (2022). https:\/\/doi.org\/10.1016\/j.matcom.2022.02.030","journal-title":"Math. Comput. Simul"},{"key":"2973_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.apacoust.2019.107142","volume":"161","author":"V Patel","year":"2020","unstructured":"V. Patel, N.V. George, Multi-channel spline adaptive filters for nonlinear active noise control. Appl. Acoust. 161, 107142 (2020). https:\/\/doi.org\/10.1016\/j.apacoust.2019.107142","journal-title":"Appl. Acoust."},{"issue":"3","key":"2973_CR30","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/JBHI.2013.2253614","volume":"17","author":"H Peng","year":"2013","unstructured":"H. Peng, B. Hu, Q. Shi, M. Ratcliffe, Q. Zhao, Y. Qi, G. Gao, Removal of ocular artifacts in EEG-an improved approach combining DWT and ANC for portable applications. IEEE J. Biomed. Heal. Inf. 17(3), 600\u2013607 (2013). https:\/\/doi.org\/10.1109\/JBHI.2013.2253614","journal-title":"IEEE J. Biomed. Heal. Inf."},{"issue":"9","key":"2973_CR31","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1002\/acs.3110","volume":"34","author":"M Ranjbar","year":"2020","unstructured":"M. Ranjbar, M. Mikaeili, A.K. Banaraki, Single-trial estimation of event-related potential components using spatiotemporal filtering and artificial bee colony optimized Gaussian kernel mixture model. Int. J. Adapt. Control Signal Process. 34(9), 1\u201313 (2020). https:\/\/doi.org\/10.1002\/acs.3110","journal-title":"Int. J. Adapt. Control Signal Process."},{"issue":"4","key":"2973_CR32","doi-asserted-by":"publisher","first-page":"772","DOI":"10.1016\/j.sigpro.2012.09.021","volume":"93","author":"M Scarpiniti","year":"2013","unstructured":"M. Scarpiniti, D. Comminiello, R. Parisi, A. Uncini, Nonlinear spline adaptive filtering. Signal Process. 93(4), 772\u2013783 (2013). https:\/\/doi.org\/10.1016\/j.sigpro.2012.09.021","journal-title":"Signal Process."},{"issue":"7","key":"2973_CR33","doi-asserted-by":"publisher","first-page":"1825","DOI":"10.1109\/TCSI.2015.2423791","volume":"62","author":"M Scarpiniti","year":"2015","unstructured":"M. Scarpiniti, D. Comminiello, R. Parisi, Novel cascade spline architectures for the identification of nonlinear systems. IEEE Trans. Circuits Syst. I Regul. Pap. 62(7), 1825\u20131835 (2015). https:\/\/doi.org\/10.1109\/TCSI.2015.2423791","journal-title":"IEEE Trans. Circuits Syst. I Regul. Pap."},{"issue":"1","key":"2973_CR34","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.clinph.2006.09.003","volume":"118","author":"A Schlogl","year":"2007","unstructured":"A. Schlogl, C. Keinrath, D. Zimmermann, R. Scherer, R. Leeb, G. Pfurtscheller, A fully automated correction method of EOG artifacts in EEG recordings. Clin. Neurophysiol. 118(1), 98\u2013104 (2007). https:\/\/doi.org\/10.1016\/j.clinph.2006.09.003","journal-title":"Clin. Neurophysiol."},{"issue":"3","key":"2973_CR35","doi-asserted-by":"publisher","first-page":"488","DOI":"10.1109\/TITB.2012.2188536","volume":"16","author":"KT Sweeney","year":"2012","unstructured":"K.T. Sweeney, T.E. Ward, S.F. McLoone, Artifact removal in physiological signals: practices and possibilities. IEEE Trans. Inf. Technol. Biomed. 16(3), 488\u2013500 (2012). https:\/\/doi.org\/10.1109\/TITB.2012.2188536","journal-title":"IEEE Trans. Inf. Technol. Biomed."},{"key":"2973_CR36","doi-asserted-by":"publisher","unstructured":"D. Szibbo, A. Luo, T. J Sullivan (2012) Removal of blink artifacts in single-channel EEG. In: Proc. Annu. Int. Conf. IEEE Eng. Med. Biol. Soc. EMBS. https:\/\/doi.org\/10.1109\/EMBC.2012.6346723","DOI":"10.1109\/EMBC.2012.6346723"},{"key":"2973_CR37","doi-asserted-by":"publisher","DOI":"10.3389\/fnins.2012.00055","author":"M Tangermann","year":"2012","unstructured":"M. Tangermann, K.R. Muller, A. Aertsen, N. Birbaumer, C. Braun, C. Brunner, R. Leeb, C. Mehring, K.J. Miller, G.R. MullerPutz, G. Nolte, G. Pfurtscheller, H. Preissl, G. Schalk, A. Schlgl, C. Vidaurre, S. Waldert, B. Blankertz, Review of the BCI competition IV. Front. Neurosci. (2012). https:\/\/doi.org\/10.3389\/fnins.2012.00055","journal-title":"Front. Neurosci."},{"issue":"2","key":"2973_CR38","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/j.cmpb.2006.06.003","volume":"83","author":"AR Teixeira","year":"2006","unstructured":"A.R. Teixeira, A.M. Tom\u00e9, E.W. Lang, P. Gruber, A. da Martins Silva, Automatic removal of high-amplitude artefacts from single-channel electroencephalograms. Comput. Methods Progr. Biomed. 83(2), 125\u2013138 (2006). https:\/\/doi.org\/10.1016\/j.cmpb.2006.06.003","journal-title":"Comput. Methods Progr. Biomed."},{"issue":"7","key":"2973_CR39","doi-asserted-by":"publisher","first-page":"1881","DOI":"10.1109\/TSP.2015.2477059","volume":"64","author":"N Tengtrairat","year":"2016","unstructured":"N. Tengtrairat, W.L. Woo, S.S. Dlay, B. Gao, Online noisy single-channel source separation using adaptive spectrum amplitude estimator and masking. IEEE Trans. Signal Process. 64(7), 1881\u20131895 (2016). https:\/\/doi.org\/10.1109\/TSP.2015.2477059","journal-title":"IEEE Trans. Signal Process."},{"issue":"4","key":"2973_CR40","doi-asserted-by":"publisher","first-page":"472","DOI":"10.1111\/j.1469-8986.1982.tb02509.x","volume":"19","author":"R Verleger","year":"1982","unstructured":"R. Verleger, T. Gasser, J. M\u00f6cks, Correction of EOG artifacts in event-related potentials of the EEG: aspects of reliability and validity. Psychophysiology 19(4), 472\u2013481 (1982)","journal-title":"Psychophysiology"},{"issue":"1\u20132","key":"2973_CR41","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/0301-0511(83)90059-5","volume":"16","author":"JC Woestenburg","year":"1983","unstructured":"J.C. Woestenburg, M.N. Verbaten, J.L. Slangen, The removal of the eye-movement artifact from the EEG by regression analysis in the frequency domain. Biol. Psychol. 16(1\u20132), 127\u2013147 (1983). https:\/\/doi.org\/10.1016\/0301-0511(83)90059-5","journal-title":"Biol. Psychol."},{"issue":"1","key":"2973_CR42","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1142\/S1793536909000047","volume":"1","author":"Z Wu","year":"2009","unstructured":"Z. Wu, N.E. Huang, Ensemble empirical mode decomposition: a noise-assisted data analysis method. Adv. Adapt. Data Anal. 1(1), 1\u201341 (2009)","journal-title":"Adv. Adapt. Data Anal."},{"key":"2973_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.103427","volume":"73","author":"S Yadav","year":"2022","unstructured":"S. Yadav, S.K. Saha, R. Kar, D. Mandal, EEG\/ERP signal enhancement through an optimally tuned adaptive filter based on marine predators\u2019 algorithm. Biomed. Signal Process. Control 73, 103427 (2022). https:\/\/doi.org\/10.1016\/j.bspc.2021.103427","journal-title":"Biomed. Signal Process. Control"},{"key":"2973_CR44","doi-asserted-by":"publisher","first-page":"4096","DOI":"10.1007\/s00034-023-02302-9","volume":"42","author":"S Yadav","year":"2023","unstructured":"S. Yadav, S.K. Saha, R. Kar, D. Mandal, Noise confiscation from sEMG through enhanced adaptive filtering based on evolutionary computing. Circuits Syst Signal Process. 42, 4096\u20134128 (2023). https:\/\/doi.org\/10.1007\/s00034-023-02302-9","journal-title":"Circuits Syst Signal Process."},{"key":"2973_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.102830","volume":"69","author":"S Yadav","year":"2021","unstructured":"S. Yadav, S.K. Saha, R. Kar, D. Mandal, Optimised adaptive noise canceller for denoising cardiovascular signal using SOS algorithm. Biomed. Signal Process. Control 69, 102830 (2021). https:\/\/doi.org\/10.1016\/j.bspc.2021.102830","journal-title":"Biomed. Signal Process. Control"},{"key":"2973_CR46","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2023.105213","volume":"86","author":"S Yadav","year":"2023","unstructured":"S. Yadav, S.K. Saha, R. Kar, An application of the Kalman filter for EEG\/ERP signal enhancement with the autoregressive realisation. Biomed. Signal Process. Control 86, 105213 (2023). https:\/\/doi.org\/10.1016\/j.bspc.2023.105213","journal-title":"Biomed. Signal Process. Control"},{"key":"2973_CR47","doi-asserted-by":"publisher","first-page":"1441","DOI":"10.1007\/s12530-024-09569-6","volume":"15","author":"S Yadav","year":"2024","unstructured":"S. Yadav, S.K. Saha, R. Kar, Design of efficient Wiener spline adaptive filter for electrocardiogram signal enrichment. Evol. Syst. 15, 1441\u20131457 (2024). https:\/\/doi.org\/10.1007\/s12530-024-09569-6","journal-title":"Evol. Syst."},{"key":"2973_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.119732","volume":"221","author":"S Yadav","year":"2023","unstructured":"S. Yadav, S.K. Saha, R. Kar, Design of robust adaptive Volterra noise mitigation architecture for sEMG signals using metaheuristic approach. Expert Syst. Appl. 221, 119732 (2023). https:\/\/doi.org\/10.1016\/j.eswa.2023.119732","journal-title":"Expert Syst. Appl."},{"key":"2973_CR49","doi-asserted-by":"publisher","first-page":"4011912","DOI":"10.1109\/TIM.2023.3324345","volume":"72","author":"S Yadav","year":"2023","unstructured":"S. Yadav, S.K. Saha, R. Kar, Evolutionary algorithm-based optimal wiener-adaptive filter design: an application on EEG noise mitigation. IEEE Trans. Instrum. Meas. 72, 4011912 (2023). https:\/\/doi.org\/10.1109\/TIM.2023.3324345","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"4","key":"2973_CR50","doi-asserted-by":"publisher","first-page":"1699","DOI":"10.1007\/s00034-020-01544-1","volume":"40","author":"YB Zhao","year":"2021","unstructured":"Y.B. Zhao, T. Yan, W.Y. Chen, H.Z. Lu, A collaborative spline adaptive filter for nonlinear echo cancellation. Circuits Syst Signal Process. 40(4), 1699\u20131719 (2021). https:\/\/doi.org\/10.1007\/s00034-020-01544-1","journal-title":"Circuits Syst Signal Process."}],"container-title":["Circuits, Systems, and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-024-02973-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00034-024-02973-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-024-02973-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,19]],"date-time":"2025-04-19T02:50:01Z","timestamp":1745031001000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00034-024-02973-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,9]]},"references-count":50,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2025,5]]}},"alternative-id":["2973"],"URL":"https:\/\/doi.org\/10.1007\/s00034-024-02973-y","relation":{},"ISSN":["0278-081X","1531-5878"],"issn-type":[{"value":"0278-081X","type":"print"},{"value":"1531-5878","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,9]]},"assertion":[{"value":"1 February 2023","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 December 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 December 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}