{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,15]],"date-time":"2025-08-15T00:45:59Z","timestamp":1755218759271,"version":"3.43.0"},"reference-count":25,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2027,4,23]],"date-time":"2027-04-23T00:00:00Z","timestamp":1808438400000},"content-version":"am","delay-in-days":508,"URL":"http:\/\/www.elsevier.com\/open-access\/userlicense\/1.0\/"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T00:00:00Z","timestamp":1764547200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100002241","name":"Japan Science and Technology Agency","doi-asserted-by":"publisher","award":["JPMJSP2119"],"award-info":[{"award-number":["JPMJSP2119"]}],"id":[{"id":"10.13039\/501100002241","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Journal of Computational and Applied Mathematics"],"published-print":{"date-parts":[[2025,12]]},"DOI":"10.1016\/j.cam.2025.116703","type":"journal-article","created":{"date-parts":[[2025,4,19]],"date-time":"2025-04-19T02:27:09Z","timestamp":1745029629000},"page":"116703","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Computationally efficient selection criterion of initial equation in STLN-based structured low-rank approximation"],"prefix":"10.1016","volume":"470","author":[{"ORCID":"https:\/\/orcid.org\/0009-0007-7186-098X","authenticated-orcid":false,"given":"Natsuki","family":"Yoshino","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Akira","family":"Tanaka","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"year":"2018","series-title":"Low Rank Approximation: Algorithms, Implementation, Applications","author":"Markovsky","key":"10.1016\/j.cam.2025.116703_b1"},{"key":"10.1016\/j.cam.2025.116703_b2","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/978-3-7643-7984-1_5","article-title":"Structured low rank approximation of a sylvester matrix","volume":"41","author":"Kaltofen","year":"2007","journal-title":"Trends Math."},{"key":"10.1016\/j.cam.2025.116703_b3","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1137\/S0895479893258802","article-title":"Total least norm formulation and solution for structured problems","volume":"17","author":"Rosen","year":"1996","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"10.1016\/j.cam.2025.116703_b4","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s10092-012-0053-5","article-title":"Two methods for the calculation of the degree of an approximate greatest common divisor of two inexact polynomials","volume":"49","author":"Winkler","year":"2012","journal-title":"Calcolo"},{"key":"10.1016\/j.cam.2025.116703_b5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.cam.2007.03.018","article-title":"Structured total least norm and approximate GCDs of inexact polynomials","volume":"215","author":"Winkler","year":"2008","journal-title":"J. Comput. Appl. Math."},{"key":"10.1016\/j.cam.2025.116703_b6","series-title":"Latent Variable Analysis and Signal Separation","first-page":"99","article-title":"Applications of polynomial common factor computation in signal processing","author":"Markovsky","year":"2018"},{"key":"10.1016\/j.cam.2025.116703_b7","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.laa.2020.11.016","article-title":"A gradient system approach for Hankel structured low-rank approximation","volume":"623","author":"Fazzi","year":"2021","journal-title":"Linear Algebra Appl."},{"key":"10.1016\/j.cam.2025.116703_b8","doi-asserted-by":"crossref","DOI":"10.1002\/nla.2428","article-title":"Fast and stable modification of the Gauss-Newton method for low-rank signal estimation","volume":"29","author":"Zvonarev","year":"2022","journal-title":"Numer. Linear Algebra Appl."},{"key":"10.1016\/j.cam.2025.116703_b9","first-page":"12847","article-title":"Identification of forward and feedback transfer functions in closed-loop systems with feedback delay","volume":"50","author":"De Iuliis","year":"2017","journal-title":"IFAC- Pap."},{"key":"10.1016\/j.cam.2025.116703_b10","doi-asserted-by":"crossref","unstructured":"A. Fazzi, N. Guglielmi, I. Markovsky, Computing common factors of matrix polynomials with applications in system and control theory, in: 2019 IEEE 58th Conference on Decision and Control, CDC, 2019, pp. 7721\u20137726.","DOI":"10.1109\/CDC40024.2019.9030137"},{"key":"10.1016\/j.cam.2025.116703_b11","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1109\/29.1488","article-title":"Signal enhancement-a composite property mapping algorithm","volume":"36","author":"Cadzow","year":"1988","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"10.1016\/j.cam.2025.116703_b12","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10208-015-9256-x","article-title":"A quadratically convergent algorithm for structured low-rank approximation","volume":"16","author":"Schost","year":"2016","journal-title":"Found. Comput. Math."},{"key":"10.1016\/j.cam.2025.116703_b13","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.1137\/130931655","article-title":"Factorization approach to structured low-rank approximation with applications","volume":"35","author":"Ishteva","year":"2014","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"10.1016\/j.cam.2025.116703_b14","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1016\/j.cam.2013.04.034","article-title":"Variable projection for affinely structured low-rank approximation in weighted 2-norms","volume":"272","author":"Usevich","year":"2014","journal-title":"J. Comput. Appl. Math."},{"key":"10.1016\/j.cam.2025.116703_b15","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.tcs.2017.03.028","article-title":"Variable projection methods for approximate (greatest) common divisor computations","volume":"681","author":"Usevich","year":"2017","journal-title":"Theoret. Comput. Sci."},{"key":"10.1016\/j.cam.2025.116703_b16","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1007\/s40819-021-01162-8","article-title":"Structured low-rank approximation: Optimization on matrix manifold approach","volume":"7","author":"Saha","year":"2021","journal-title":"Int. J. Appl. Comput. Math."},{"key":"10.1016\/j.cam.2025.116703_b17","doi-asserted-by":"crossref","first-page":"287","DOI":"10.4310\/22-SII735","article-title":"Hankel low-rank approximation and completion in time series analysis and forecasting: a brief review","volume":"16","author":"Gillard","year":"2023","journal-title":"Stat. Interface"},{"key":"10.1016\/j.cam.2025.116703_b18","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1016\/j.jsc.2019.08.004","article-title":"Toward the best algorithm for approximate GCD of univariate polynomials","volume":"105","author":"Nagasaka","year":"2021","journal-title":"J. Symbolic Comput."},{"key":"10.1016\/j.cam.2025.116703_b19","doi-asserted-by":"crossref","first-page":"757","DOI":"10.1023\/A:1022347425533","article-title":"Low rank approximation of a Hankel matrix by structured total least norm","volume":"39","author":"Park","year":"1999","journal-title":"BIT Numer. Math."},{"key":"10.1016\/j.cam.2025.116703_b20","first-page":"601","article-title":"Generalized inverse of a matrix and its applications","author":"Rao","year":"1972","journal-title":"Berkeley Symp. Math. Stat. Probab."},{"key":"10.1016\/j.cam.2025.116703_b21","first-page":"14","article-title":"Structured total least norm for nonlinear problems","volume":"20","author":"Rosen","year":"1998","journal-title":"Soc. Ind. Appl. Math."},{"year":"1996","series-title":"Matrix Computations","author":"Golub","key":"10.1016\/j.cam.2025.116703_b22"},{"year":"2022","series-title":"MATLAB version: 9.13.0 (R2022b)","author":"Inc.","key":"10.1016\/j.cam.2025.116703_b23"},{"issue":"3\/4","key":"10.1016\/j.cam.2025.116703_b24","doi-asserted-by":"crossref","first-page":"170","DOI":"10.1145\/2576802.2576829","article-title":"NAClab: a Matlab toolbox for numerical algebraic computation","volume":"47","author":"Zeng","year":"2014","journal-title":"ACM Commun. Comput. Algebra"},{"issue":"4","key":"10.1016\/j.cam.2025.116703_b25","doi-asserted-by":"crossref","first-page":"582","DOI":"10.1016\/j.ijforecast.2018.03.008","article-title":"Structured low-rank matrix completion for forecasting in time series analysis","volume":"34","author":"Gillard","year":"2018","journal-title":"Int. J. Forecast."}],"container-title":["Journal of Computational and Applied Mathematics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0377042725002171?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0377042725002171?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T11:37:15Z","timestamp":1754480235000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0377042725002171"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12]]},"references-count":25,"alternative-id":["S0377042725002171"],"URL":"https:\/\/doi.org\/10.1016\/j.cam.2025.116703","relation":{},"ISSN":["0377-0427"],"issn-type":[{"type":"print","value":"0377-0427"}],"subject":[],"published":{"date-parts":[[2025,12]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Computationally efficient selection criterion of initial equation in STLN-based structured low-rank approximation","name":"articletitle","label":"Article Title"},{"value":"Journal of Computational and Applied Mathematics","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cam.2025.116703","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 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":"116703"}}