{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,25]],"date-time":"2025-06-25T04:12:52Z","timestamp":1750824772032,"version":"3.41.0"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319606170"},{"type":"electronic","value":"9783319606187"}],"license":[{"start":{"date-parts":[[2017,8,19]],"date-time":"2017-08-19T00:00:00Z","timestamp":1503100800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-60618-7_36","type":"book-chapter","created":{"date-parts":[[2017,8,18]],"date-time":"2017-08-18T12:18:30Z","timestamp":1503058710000},"page":"364-374","source":"Crossref","is-referenced-by-count":4,"title":["Expectation Maximization Based PCA and Hessian LLE with Suitable Post Classifiers for Epilepsy Classification from EEG Signals"],"prefix":"10.1007","author":[{"given":"Sunil Kumar","family":"Prabhakar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Harikumar","family":"Rajaguru","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,8,19]]},"reference":[{"key":"36_CR1","unstructured":"Prabhakar, S.K., Rajaguru, H.: ICA, LGE and FMI as dimensionality reduction techniques followed by GMM as post classifier for the classification of epilepsy risk levels from EEG signals. In: Proceedings of the 9th IEEE European Modelling Symposium, Madrid, Spain, 6\u20138 October, pp. 1\u20135 (2015)"},{"key":"36_CR2","doi-asserted-by":"crossref","unstructured":"Prabhakar, S.K., Rajaguru, H.: Application of linear graph embedding as a dimensionality reduction technique and sparse representation classifier as a post classifier for the classification of epilepsy risk levels from EEG signals. In: Proceedings of the International Conference on Graphic and Image Processing (ICGIP), Singapore, 23\u201325 October 2015","DOI":"10.1117\/12.2227989"},{"key":"36_CR3","doi-asserted-by":"crossref","unstructured":"Prabhakar, S.K., Rajaguru, H.: A different approach to epilepsy risk level classification utilizing various distance measures as post classifiers. In: Proceedings of the 8th Biomedical Engineering International Conference (BMEiCON), Pattaya, Thailand, 25\u201327 November 2015","DOI":"10.1109\/BMEiCON.2015.7399570"},{"key":"36_CR4","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/TBME.2004.839630","volume":"52","author":"N Acir","year":"2005","unstructured":"Acir, N., Oztura, I., Kuntalp, M., Baklan, B., Guzelis, C.: Automatic detection of epileptiform events in EEG by a three-stage procedure based on artificial neural networks. IEEE Trans. Biomed. Eng. 52, 30\u201340 (2005)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"36_CR5","first-page":"175","volume":"40","author":"M Adjouadi","year":"2004","unstructured":"Adjouadi, M., Cabrerizo, M., Ayala, M., Sanchez, D., Yaylali, I., Jayakar, P., Barreto, A.: A new mathematical approach based on orthogonal operators for the detection of interictal spikes in epileptogenic data. Biomed. Sci. Instrum. 40, 175\u2013180 (2004)","journal-title":"Biomed. Sci. Instrum."},{"key":"36_CR6","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/0013-4694(80)90312-0","volume":"48","author":"JS Barlow","year":"1980","unstructured":"Barlow, J.S.: EEG transient detection by matched inverse digital filtering. Electroencephalogr. Clin. Neurophysiol. 48, 246\u2013248 (1980)","journal-title":"Electroencephalogr. Clin. Neurophysiol."},{"issue":"4","key":"36_CR7","doi-asserted-by":"publisher","first-page":"171","DOI":"10.12988\/astp.2015.5117","volume":"9","author":"SK Prabhakar","year":"2015","unstructured":"Prabhakar, S.K., Rajaguru, H.: Analysis of centre tendency mode chaotic modeling for electroencephalography signals obtained from an epileptic patient. Adv. Stud. Theor. Phys. 9(4), 171\u2013177 (2015). doi: 10.12988\/astp.2015.5117 . HIKARI Ltd.","journal-title":"Adv. Stud. Theor. Phys."},{"key":"36_CR8","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1007\/BF02441427","volume":"27","author":"BL Davey","year":"1989","unstructured":"Davey, B.L., Fright, W.R., Carroll, G.J., Jones, R.D.: Expert system approach to detection of epileptiform activity in the EEG. Med. Biol. Eng. Compu. 27, 365\u2013370 (1989)","journal-title":"Med. Biol. Eng. Compu."},{"key":"36_CR9","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.1109\/10.250582","volume":"40","author":"A Dingle","year":"1993","unstructured":"Dingle, A., Jones, R., Carroll, G., Fright, W.: A multistage system to detect epileptiform activity in the EEG. IEEE Trans. Biomed. Eng. 40, 1260\u20131268 (1993)","journal-title":"IEEE Trans. Biomed. Eng."},{"key":"36_CR10","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1016\/j.jneumeth.2005.04.013","volume":"148","author":"I Guler","year":"2005","unstructured":"Guler, I., Ubeyli, E.D.: Adaptive neuro-fuzzy inference system for classification of EEG signals using wavelet coefficients. J. Neurosci. Methods 148, 113\u2013121 (2005)","journal-title":"J. Neurosci. Methods"},{"key":"36_CR11","doi-asserted-by":"crossref","first-page":"1909","DOI":"10.1016\/j.clinph.2009.08.007","volume":"120","author":"JJ Halford","year":"2009","unstructured":"Halford, J.J.: Computerized epileptiform transient detection in the scalp electroencephalogram: obstacles to progress and the example of computerized ECG interpretation. Clin. Neurophysiol. 120, 1909\u20131915 (2009)","journal-title":"Clin. Neurophysiol."},{"key":"36_CR12","doi-asserted-by":"crossref","first-page":"1557","DOI":"10.1109\/TBME.2002.805477","volume":"49","author":"H Liu","year":"2002","unstructured":"Liu, H., Zhang, T., Yang, F.: A multistage multimethod approach for automatic detection and classification of epileptiform EEG. IEEE Trans. Biomed. Eng. 49, 1557\u20131566 (2002)","journal-title":"IEEE Trans. Biomed. Eng."},{"issue":"50","key":"36_CR13","first-page":"2451","volume":"9","author":"R Harikumar","year":"2015","unstructured":"Harikumar, R., Kumar, P.S.: Frequency behaviors of electroencephalography signals in epileptic patients from a wavelet thresholding perspective. Appl. Math. Sci. 9(50), 2451\u20132457 (2015). HIKARI Ltd.","journal-title":"Appl. Math. Sci."},{"issue":"1","key":"36_CR14","doi-asserted-by":"crossref","first-page":"3164","DOI":"10.1023\/A:1015491123070","volume":"12","author":"DE Cragar","year":"2002","unstructured":"Cragar, D.E., Berry, D.T., Fakhoury, T.A., Cibula, J.E., Schmitt, F.A.: A review of diagnostic techniques in the differential diagnosis of epileptic and nonepileptic seizures. Neuropsychol. Rev. 12(1), 3164 (2002)","journal-title":"Neuropsychol. Rev."},{"key":"36_CR15","doi-asserted-by":"crossref","first-page":"12, 28","DOI":"10.1109\/TMI.2004.837363","volume":"24","author":"J Kybic","year":"2005","unstructured":"Kybic, J., Clerc, M., Abboud, T., Faugeras, O., Keriven, R., Papadopoulo, T.: A common formalism for the integral formulations of the forward EEG problem. IEEE Trans. Med. Imaging 24, 12, 28 (2005)","journal-title":"IEEE Trans. Med. Imaging"},{"issue":"11","key":"36_CR16","doi-asserted-by":"crossref","first-page":"e189","DOI":"10.1111\/j.1528-1167.2012.03653.x","volume":"53","author":"WT Kerr","year":"2012","unstructured":"Kerr, W.T., Anderson, A., Lau, E.P., Cho, A.Y., Xia, H., Bramen, J., Douglas, P.K., Braun, E.S., Stern, J.M., Cohen, M.S.: Automated diagnosis of epilepsy using EEG power spectrum. Epilepsia 53(11), e189 (2012)","journal-title":"Epilepsia"},{"issue":"s2","key":"36_CR17","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1111\/j.0013-9580.2004.452002.x","volume":"45","author":"C LaFrance","year":"2004","unstructured":"LaFrance, C., Devinsky, O.: The treatment of nonepileptic seizures: historical perspectives and future directions. Epilepsia 45(s2), 15 (2004)","journal-title":"Epilepsia"},{"key":"36_CR18","doi-asserted-by":"crossref","unstructured":"Michael, T., Christopher, B.: Mixtures of probabilistic principal component analyzers. Technical report NCRG\/97\/003, Neural Computing Research Group, Aston University, June 1997","DOI":"10.1049\/cp:19970694"},{"key":"36_CR19","doi-asserted-by":"crossref","unstructured":"Donoho, D.L., Grimes, C.: Hessian eigenmaps: new locally linear embedding techniques for high-dimensional data. In: Proceedings of National Academy of Science of the United States of America, pp. 5591\u20135596 (2003)","DOI":"10.1073\/pnas.1031596100"},{"key":"36_CR20","first-page":"57","volume":"10","author":"S Cost","year":"1993","unstructured":"Cost, S., Salzberg, S.: A weighted nearest neighbor algorithm for learning with symbolic features. Mach. Learn. 10, 57\u201378 (1993)","journal-title":"Mach. Learn."},{"key":"36_CR21","doi-asserted-by":"crossref","unstructured":"Platt, J.C.: Fast training of support vector machines using sequential minimum optimization. In: Sch\u04e7lkopf, B., Burges, C.J.C., Smola, A.J. (eds.) Advances in Kernel Methods \u2013 Support Vector Learning, pp. 185\u2013208. MIT Press, Cambridge (1998)","DOI":"10.7551\/mitpress\/1130.003.0016"}],"container-title":["Advances in Intelligent Systems and Computing","Proceedings of the Eighth International Conference on Soft Computing and Pattern Recognition (SoCPaR 2016)"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-60618-7_36","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T23:26:28Z","timestamp":1750807588000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-60618-7_36"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,19]]},"ISBN":["9783319606170","9783319606187"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-60618-7_36","relation":{},"ISSN":["2194-5357","2194-5365"],"issn-type":[{"type":"print","value":"2194-5357"},{"type":"electronic","value":"2194-5365"}],"subject":[],"published":{"date-parts":[[2017,8,19]]}}}