{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T14:33:19Z","timestamp":1777127599477,"version":"3.51.4"},"reference-count":40,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,4,13]],"date-time":"2027-04-13T00:00:00Z","timestamp":1807574400000},"content-version":"am","delay-in-days":224,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T00:00:00Z","timestamp":1788220800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Signal Processing"],"published-print":{"date-parts":[[2026,9]]},"DOI":"10.1016\/j.sigpro.2026.110633","type":"journal-article","created":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T07:42:50Z","timestamp":1775720570000},"page":"110633","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["An MM estimation algorithm for independent component analysis"],"prefix":"10.1016","volume":"246","author":[{"given":"Xun-Jian","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hua","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kenneth","family":"Lange","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0001","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/0165-1684(94)90029-9","article-title":"Independent component analysis, a new concept?","volume":"36","author":"Comon","year":"1994","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2026.110633_bib0002","series-title":"Natural Image Statistics: A Probabilistic Approach to Early Computational Vision","first-page":"151","article-title":"Independent component analysis","author":"Hyv\u00e4rinen","year":"2001"},{"issue":"23","key":"10.1016\/j.sigpro.2026.110633_bib0003","doi-asserted-by":"crossref","first-page":"3327","DOI":"10.1016\/S0042-6989(97)00121-1","article-title":"The \u201cindependent components\u201d of natural scenes are edge filters","volume":"37","author":"Bell","year":"1997","journal-title":"Vision Res."},{"key":"10.1016\/j.sigpro.2026.110633_bib0004","series-title":"2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing","first-page":"1","article-title":"Improvement of remote sensing multispectral image classification by using independent component analysis","author":"Karoui","year":"2009"},{"issue":"6","key":"10.1016\/j.sigpro.2026.110633_bib0005","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1080\/01431160701395211","article-title":"Applications of ICA for the enhancement and classification of polarimetric SAR images","volume":"29","author":"Wang","year":"2008","journal-title":"Int. J. Remote Sens."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0006","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1109\/TCE.2007.4341582","article-title":"Improving fusion of surveillance images in sensor networks using independent component analysis","volume":"53","author":"Cvejic","year":"2007","journal-title":"IEEE Trans. Consum. Electron."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0007","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/S0165-1684(01)00194-3","article-title":"Advanced ICA-based receivers for block fading DS-CDMA channels","volume":"82","author":"Ristaniemi","year":"2002","journal-title":"Signal Process."},{"key":"10.1016\/j.sigpro.2026.110633_bib0008","first-page":"894","article-title":"Extended ICA removes artifacts from electroencephalographic recordings","volume":"10","author":"Jung","year":"1997","journal-title":"Adv. Neural Inf. Process. Syst."},{"issue":"4-5","key":"10.1016\/j.sigpro.2026.110633_bib0009","doi-asserted-by":"crossref","first-page":"411","DOI":"10.1016\/S0893-6080(00)00026-5","article-title":"Independent component analysis: algorithms and applications","volume":"13","author":"Hyv\u00e4rinen","year":"2000","journal-title":"Neural Netw."},{"issue":"8","key":"10.1016\/j.sigpro.2026.110633_bib0010","doi-asserted-by":"crossref","first-page":"1875","DOI":"10.1162\/089976699300015990","article-title":"Natural gradient learning for over-and under-complete bases in ICA","volume":"11","author":"Amari","year":"1999","journal-title":"Neural Comput."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0011","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1109\/72.761722","article-title":"Fast and robust fixed-point algorithms for independent component analysis","volume":"10","author":"Hyvarinen","year":"1999","journal-title":"IEEE Trans. Neural Netw."},{"issue":"7","key":"10.1016\/j.sigpro.2026.110633_bib0012","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.1162\/neco.1997.9.7.1483","article-title":"A fast fixed-point algorithm for independent component analysis","volume":"9","author":"Hyv\u00e4rinen","year":"1997","journal-title":"Neural Comput."},{"issue":"15","key":"10.1016\/j.sigpro.2026.110633_bib0013","doi-asserted-by":"crossref","first-page":"4040","DOI":"10.1109\/TSP.2018.2844203","article-title":"Faster independent component analysis by preconditioning with Hessian approximations","volume":"66","author":"Ablin","year":"2018","journal-title":"IEEE Trans. Signal Process."},{"key":"10.1016\/j.sigpro.2026.110633_bib0014","series-title":"4th International Symposium on Independent Component Analysis and Blind Signal Separation (ICA2003), April 2003, Nara, Japan","first-page":"897","article-title":"Blind source separation with relative Newton method","volume":"2003","author":"Zibulevsky","year":"2003"},{"key":"10.1016\/j.sigpro.2026.110633_bib0015","series-title":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","first-page":"1805","article-title":"Newton method for the ICA mixture model","author":"Palmer","year":"2008"},{"key":"10.1016\/j.sigpro.2026.110633_bib0016","series-title":"International Conference on Acoustics, Speech, and Signal Processing,","first-page":"2109","article-title":"Source separation using higher order moments","author":"Cardoso","year":"1989"},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0017","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1214\/15-STS520","article-title":"Fourth moments and independent component analysis","volume":"30","author":"Miettinen","year":"2015","journal-title":"Stat. Sci."},{"key":"10.1016\/j.sigpro.2026.110633_bib0018","series-title":"IEE Proceedings F (Radar and Signal Processing)","first-page":"362","article-title":"Blind beamforming for non\u2013Gaussian signals","volume":"140","author":"Cardoso","year":"1993"},{"key":"10.1016\/j.sigpro.2026.110633_bib0019","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1016\/j.sigpro.2016.08.015","article-title":"Majorization\u2013minimization for blind source separation of sparse sources","volume":"131","author":"Mourad","year":"2017","journal-title":"Signal Process."},{"issue":"1","key":"10.1016\/j.sigpro.2026.110633_bib0020","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1177\/096228029700600104","article-title":"EM algorithms without missing data","volume":"6","author":"Becker","year":"1997","journal-title":"Stat. Methods Med. Res."},{"issue":"1","key":"10.1016\/j.sigpro.2026.110633_bib0021","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1198\/0003130042836","article-title":"A tutorial on MM algorithms","volume":"58","author":"Hunter","year":"2004","journal-title":"Am. Stat."},{"issue":"1","key":"10.1016\/j.sigpro.2026.110633_bib0022","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1080\/10618600.2000.10474858","article-title":"Optimization transfer using surrogate objective functions","volume":"9","author":"Lange","year":"2000","journal-title":"J. Comput. Graphical Stat."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0023","doi-asserted-by":"crossref","first-page":"794","DOI":"10.1109\/TSP.2016.2601299","article-title":"Majorization-minimization algorithms in signal processing, communications, and machine learning","volume":"65","author":"Sun","year":"2016","journal-title":"IEEE Trans. Signal Process."},{"issue":"4","key":"10.1016\/j.sigpro.2026.110633_bib0024","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1007\/BF00049423","article-title":"Monotonicity of quadratic-approximation algorithms","volume":"40","author":"B\u00f6hning","year":"1988","journal-title":"Ann. Inst. Stat. Math."},{"key":"10.1016\/j.sigpro.2026.110633_bib0025","series-title":"Computational Statistics in Data Science","first-page":"1","article-title":"Nonconvex optimization via MM algorithms: convergence theory","author":"Lange","year":"2021"},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0026","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1109\/TAC.1980.1102343","article-title":"Robust identification of a nonminimum phase system: blind adjustment of a linear equalizer in data communications","volume":"25","author":"Benveniste","year":"1980","journal-title":"IEEE Trans. Automat. Control"},{"key":"10.1016\/j.sigpro.2026.110633_bib0027","series-title":"MM Optimization Algorithms","author":"Lange","year":"2016"},{"key":"10.1016\/j.sigpro.2026.110633_bib0028","series-title":"4th Joint Symposium on Neural Computation Proceedings","first-page":"132","article-title":"Independent component analysis for mixed sub-Gaussian and super-Gaussian sources","author":"Lee","year":"1997"},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0029","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1002\/acs.2702","article-title":"Large-scale super-Gaussian sources separation using fast-ICA with rational nonlinearities","volume":"31","author":"He","year":"2017","journal-title":"Int. J. Adapt. Control Signal Process."},{"issue":"2","key":"10.1016\/j.sigpro.2026.110633_bib0030","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1162\/089976699300016719","article-title":"Independent component analysis using an extended infomax algorithm for mixed subgaussian and supergaussian sources","volume":"11","author":"Lee","year":"1999","journal-title":"Neural Comput."},{"key":"10.1016\/j.sigpro.2026.110633_bib0031","series-title":"Inequalities: Theory of Majorization and Its Applications","author":"Marshall","year":"2011"},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0032","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1101\/gr.145821.112","article-title":"Genotype imputation via matrix completion","volume":"23","author":"Chi","year":"2013","journal-title":"Genome Res."},{"issue":"3","key":"10.1016\/j.sigpro.2026.110633_bib0033","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1214\/10-STS336","article-title":"Graphics processing units and high-dimensional optimization","volume":"25","author":"Zhou","year":"2010","journal-title":"Stat. Sci."},{"issue":"4","key":"10.1016\/j.sigpro.2026.110633_bib0034","doi-asserted-by":"crossref","first-page":"494","DOI":"10.1214\/21-STS835","article-title":"High-performance statistical computing in the computing environments of the 2020s","volume":"37","author":"Ko","year":"2022","journal-title":"Stat. Sci."},{"key":"10.1016\/j.sigpro.2026.110633_bib0035","series-title":"Numerical Optimization","author":"Nocedal","year":"2006"},{"key":"10.1016\/j.sigpro.2026.110633_bib0036","series-title":"Dokl Akad Nauk Sssr","first-page":"543","article-title":"A method for solving the convex programming problem with convergence rate O(1k2)","volume":"269","author":"Nesterov","year":"1983"},{"key":"10.1016\/j.sigpro.2026.110633_bib0037","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v076.i02","article-title":"Blind source separation based on joint diagonalization in R: the packages JADE and BSSasymp","volume":"76","author":"Miettinen","year":"2017","journal-title":"J. Stat. Software"},{"key":"10.1016\/j.sigpro.2026.110633_bib0038","doi-asserted-by":"crossref","first-page":"62","DOI":"10.3389\/fnsys.2012.00062","article-title":"The ADHD-200 consortium: a model to advance the translational potential of neuroimaging in clinical neuroscience","volume":"6","author":"Consortium","year":"2012","journal-title":"Front. Syst. Neurosci."},{"key":"10.1016\/j.sigpro.2026.110633_bib0039","doi-asserted-by":"crossref","first-page":"14","DOI":"10.3389\/fninf.2014.00014","article-title":"Machine learning for neuroimaging with scikit-learn","volume":"8","author":"Abraham","year":"2014","journal-title":"Front. Neuroinf."},{"issue":"1","key":"10.1016\/j.sigpro.2026.110633_bib0040","doi-asserted-by":"crossref","first-page":"288","DOI":"10.1016\/j.neuroimage.2010.02.010","article-title":"A group model for stable multi-subject ICA on fMRI-datasets","volume":"51","author":"Varoquaux","year":"2010","journal-title":"Neuroimage"}],"container-title":["Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165168426001477?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0165168426001477?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,25]],"date-time":"2026-04-25T13:33:17Z","timestamp":1777123997000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0165168426001477"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,9]]},"references-count":40,"alternative-id":["S0165168426001477"],"URL":"https:\/\/doi.org\/10.1016\/j.sigpro.2026.110633","relation":{},"ISSN":["0165-1684"],"issn-type":[{"value":"0165-1684","type":"print"}],"subject":[],"published":{"date-parts":[[2026,9]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"An MM estimation algorithm for independent component analysis","name":"articletitle","label":"Article Title"},{"value":"Signal Processing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.sigpro.2026.110633","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"110633"}}