{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:42:29Z","timestamp":1765546949083,"version":"3.37.3"},"reference-count":51,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T00:00:00Z","timestamp":1658448000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,7,22]],"date-time":"2022-07-22T00:00:00Z","timestamp":1658448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"name":"Key Research Project of Henan Higher Education Institutions","award":["21A413006"],"award-info":[{"award-number":["21A413006"]}]},{"DOI":"10.13039\/501100012337","name":"Nanhu Scholars Program for Young Scholars of Xinyang Normal University","doi-asserted-by":"publisher","award":["2017B67"],"award-info":[{"award-number":["2017B67"]}],"id":[{"id":"10.13039\/501100012337","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Graduate Research and Innovation Fund of Xinyang Normal University","award":["2021KYJJ44"],"award-info":[{"award-number":["2021KYJJ44"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Circuits Syst Signal Process"],"published-print":{"date-parts":[[2022,12]]},"DOI":"10.1007\/s00034-022-02116-1","type":"journal-article","created":{"date-parts":[[2022,7,21]],"date-time":"2022-07-21T23:07:46Z","timestamp":1658444866000},"page":"7117-7144","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["The Maximum Correntropy Criterion-Based Robust Hierarchical Estimation Algorithm for Linear Parameter-Varying Systems with Non-Gaussian Noise"],"prefix":"10.1007","volume":"41","author":[{"given":"Qinzhi","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6503-4066","authenticated-orcid":false,"given":"Xuehai","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,7,22]]},"reference":[{"key":"2116_CR1","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.ast.2017.03.009","volume":"66","author":"AK Al-Jiboory","year":"2017","unstructured":"A.K. Al-Jiboory, G.M. Zhu et al., LPV modeling of a flexible wing aircraft using modal alignment and adaptive gridding methods. Aerosp. Sci. Technol. 66, 92\u2013102 (2017)","journal-title":"Aerosp. Sci. Technol."},{"issue":"1\u20134","key":"2116_CR2","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/S0925-2312(01)00643-9","volume":"48","author":"C Campbell","year":"2002","unstructured":"C. Campbell, Kernel methods: a survey of current techniques. Neurocomputing 48(1\u20134), 63\u201384 (2002)","journal-title":"Neurocomputing"},{"issue":"4","key":"2116_CR3","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1504\/IJMIC.2017.087056","volume":"28","author":"L Chen","year":"2017","unstructured":"L. Chen, Y.S. Ding, Multiple model approach for nonlinear system identification with mixed-Gaussian weighting functions. Int. J. Model. Identif. Control 28(4), 295\u2013306 (2017)","journal-title":"Int. J. Model. Identif. Control"},{"issue":"3","key":"2116_CR4","doi-asserted-by":"publisher","first-page":"1497","DOI":"10.1109\/TCSII.2021.3121389","volume":"69","author":"J Chen","year":"2022","unstructured":"J. Chen, F. Ding, M.F. Hu, Q.M. Zhu, Accelerated gradient descent estimation for rational models by using Volterra series: structure identification and parameter estimation. IEEE Trans. Circuits Syst. II 69(3), 1497\u20131501 (2022)","journal-title":"IEEE Trans. Circuits Syst. II"},{"issue":"8","key":"2116_CR5","doi-asserted-by":"publisher","first-page":"5185","DOI":"10.1109\/TII.2020.3025581","volume":"17","author":"J Chen","year":"2021","unstructured":"J. Chen, B. Huang et al., Identification of two-dimensional causal systems with missing output data via expectation-maximization algorithm. IEEE Trans. Ind. Inform. 17(8), 5185\u20135196 (2021)","journal-title":"IEEE Trans. Ind. Inform."},{"key":"2116_CR6","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1016\/j.automatica.2018.08.021","volume":"97","author":"PB Cox","year":"2018","unstructured":"P.B. Cox, R. T\u00f3th, M. Petreczky, Towards efficient maximum likelihood estimation of LPV-SS models. Automatica 97, 392\u2013403 (2018)","journal-title":"Automatica"},{"issue":"16","key":"2116_CR7","doi-asserted-by":"publisher","first-page":"2681","DOI":"10.1049\/iet-cta.2018.5313","volume":"13","author":"S Djennounel","year":"2019","unstructured":"S. Djennounel, M. Bettayeb, Modulating function-based fast convergent observer and output feedback control for a class of non-linear systems. IET Control Theory Appl. 13(16), 2681\u20132693 (2019)","journal-title":"IET Control Theory Appl."},{"issue":"12","key":"2116_CR8","doi-asserted-by":"publisher","first-page":"5951","DOI":"10.1007\/s00034-020-01441-7","volume":"39","author":"SJ Fan","year":"2020","unstructured":"S.J. Fan, F. Ding, T. Hayat, Recursive identification of errors-in-variables systems based on the correlation analysis. Circuits Syst. Signal Process. 39(12), 5951\u20135981 (2020)","journal-title":"Circuits Syst. Signal Process."},{"key":"2116_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.conengprac.2021.104725","volume":"109","author":"D Gidon","year":"2021","unstructured":"D. Gidon, H.S. Abbas et al., Data-driven LPV model predictive control of a cold atmospheric plasma jet for biomaterials processing. Control Eng. Pract. 109, 104725 (2021)","journal-title":"Control Eng. Pract."},{"issue":"6","key":"2116_CR10","doi-asserted-by":"publisher","first-page":"2160","DOI":"10.1109\/TCST.2016.2642159","volume":"25","author":"A Golabi","year":"2017","unstructured":"A. Golabi, N. Meskin, R. T\u00f3th, J.A. Mohammadpour, Bayesian approach for LPV model identification and its application to complex processes. IEEE Trans. Control Syst. Technol. 25(6), 2160\u20132167 (2017)","journal-title":"IEEE Trans. Control Syst. Technol."},{"issue":"13","key":"2116_CR11","first-page":"1557","volume":"10","author":"M Hadian","year":"2021","unstructured":"M. Hadian, A. Ramezani, W.J. Zhang, Discretisation of linear parameter-varying state-space representations. Control Appl. Learn. 10(13), 1557 (2021)","journal-title":"Control Appl. Learn."},{"key":"2116_CR12","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1016\/j.jprocont.2019.12.007","volume":"86","author":"B Hadid","year":"2020","unstructured":"B. Hadid, E. Duviella, S. Lecoeuche, Data-driven modeling for river flood forecasting based on a piecewise linear ARX system identification. J. Process Control 86, 44\u201356 (2020)","journal-title":"J. Process Control"},{"issue":"5","key":"2116_CR13","doi-asserted-by":"publisher","first-page":"2302","DOI":"10.1007\/s00034-020-01593-6","volume":"40","author":"L Janjanam","year":"2021","unstructured":"L. Janjanam, S.K. Saha et al., Global gravitational search algorithm-aided Kalman filter design for Volterra-based nonlinear system identification. Circuits Syst. Signal Process. 40(5), 2302\u20132334 (2021)","journal-title":"Circuits Syst. Signal Process."},{"issue":"4","key":"2116_CR14","doi-asserted-by":"publisher","first-page":"1531","DOI":"10.3390\/s21041531","volume":"21","author":"SD Juli\u00e1n M","year":"2021","unstructured":"S.D. Juli\u00e1n M, S.L. Juli\u00e1n J et al., Autonomous ground vehicle lane-keeping LPV model-based control: dual-rate state estimation and comparison of different real-time control strategies. Sensors 21(4), 1531\u20131532 (2021)","journal-title":"Sensors"},{"key":"2116_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2020.108914","volume":"115","author":"V Laurain","year":"2020","unstructured":"V. Laurain, R. Laurain et al., Sparse RKHS estimation via globally convex optimization and its application in LPV-IO identification. Automatica 115, 108914 (2020)","journal-title":"Automatica"},{"issue":"3","key":"2116_CR16","doi-asserted-by":"publisher","first-page":"2537","DOI":"10.1007\/s11071-021-06417-z","volume":"104","author":"JM Li","year":"2021","unstructured":"J.M. Li, F. Ding, Identification methods of nonlinear systems based on the kernel functions. Nonlinear Dyn. 104(3), 2537\u20132552 (2021)","journal-title":"Nonlinear Dyn."},{"key":"2116_CR17","doi-asserted-by":"publisher","first-page":"1302","DOI":"10.1109\/LSP.2022.3177352","volume":"29","author":"JM Li","year":"2022","unstructured":"J.M. Li, F. Ding, Fitting nonlinear signal models using the increasing-data criterion. IEEE Signal Process. Lett. 29, 1302\u20131306 (2022)","journal-title":"IEEE Signal Process. Lett."},{"issue":"10","key":"2116_CR18","doi-asserted-by":"publisher","first-page":"229","DOI":"10.3390\/sym9100229","volume":"9","author":"YS Li","year":"2017","unstructured":"Y.S. Li, Y.Y. Wang, F. Albu, A general zero attraction proportionate normalized maximum correntropy criterion algorithm for sparse system identification. Symmetry 9(10), 229 (2017)","journal-title":"Symmetry"},{"issue":"1","key":"2116_CR19","doi-asserted-by":"publisher","first-page":"45","DOI":"10.3390\/e19010045","volume":"19","author":"YS Li","year":"2017","unstructured":"Y.S. Li, Y.Y. Wang, R. Yang, F. Albu, A soft parameter function penalized normalized maximum correntropy criterion algorithm for sparse system identification. Entropy 19(1), 45 (2017)","journal-title":"Entropy"},{"key":"2116_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2020.107534","volume":"172","author":"Z Li","year":"2020","unstructured":"Z. Li, L. Xing, B.D. Chen, Adaptive filtering with quantized minimum error entropy criterion. Signal Process. 172, 107534 (2020)","journal-title":"Signal Process."},{"issue":"7","key":"2116_CR21","doi-asserted-by":"publisher","first-page":"3470","DOI":"10.1007\/s00034-019-01329-1","volume":"39","author":"J Li","year":"2020","unstructured":"J. Li, T.C. Zong, J.P. Gu, L. Hua, Parameter estimation of Wiener systems based on the particle swarm iteration and gradient search principle. Circuits Syst. Signal Process. 39(7), 3470\u20133495 (2020)","journal-title":"Circuits Syst. Signal Process."},{"issue":"11","key":"2116_CR22","doi-asserted-by":"publisher","first-page":"5286","DOI":"10.1109\/TSP.2007.896065","volume":"55","author":"W Liu","year":"2007","unstructured":"W. Liu, P.P. Pokharel, J.C. Principe, Correntropy: properties and applications in non-Gaussian signal processing. IEEE Trans. Signal Process. 55(11), 5286\u20135298 (2007)","journal-title":"IEEE Trans. Signal Process."},{"key":"2116_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2022.110365","volume":"142","author":"SY Liu","year":"2022","unstructured":"S.Y. Liu, X. Zhang et al., Expectation-maximization algorithm for bilinear systems by using the Rauch\u2013Tung\u2013Striebel smoother. Automatica 142, 110365 (2022)","journal-title":"Automatica"},{"issue":"7","key":"2116_CR24","doi-asserted-by":"publisher","first-page":"3274","DOI":"10.1109\/TAC.2020.3016767","volume":"66","author":"LF Ma","year":"2020","unstructured":"L.F. Ma, Y. Zhao, Z.D. Wang, J. Hu, Q.L. Han, Probability-guaranteed envelope-constrained filtering for nonlinear systems subject to measurement outliers. IEEE Trans. Autom. Control 66(7), 3274\u20133281 (2020)","journal-title":"IEEE Trans. Autom. Control"},{"key":"2116_CR25","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.automatica.2015.01.018","volume":"53","author":"D Piga","year":"2015","unstructured":"D. Piga, P. Cox, R. T\u00f3th, V. Laurain, LPV system identification under noise corrupted scheduling and output signal observations. Automatica 53, 329\u2013338 (2015)","journal-title":"Automatica"},{"issue":"11","key":"2116_CR26","doi-asserted-by":"publisher","first-page":"5103","DOI":"10.1007\/s00034-019-01111-3","volume":"38","author":"R Pogula","year":"2019","unstructured":"R. Pogula, T.K. Kumar, F. Albu, Robust sparse normalized LMAT algorithms for adaptive system identification under impulsive noise environments. Circuits Syst. Signal Process. 38(11), 5103\u20135134 (2019)","journal-title":"Circuits Syst. Signal Process."},{"issue":"5","key":"2116_CR27","doi-asserted-by":"publisher","first-page":"454","DOI":"10.1109\/THMS.2020.2989685","volume":"50","author":"AJ Pronker","year":"2020","unstructured":"A.J. Pronker, D.A. Abbink et al., Estimating an LPV model of driver neuromuscular admittance using grip force as scheduling variable. IEEE Trans. Hum. Mach. Syst. 50(5), 454\u2013464 (2020)","journal-title":"IEEE Trans. Hum. Mach. Syst."},{"issue":"4","key":"2116_CR28","doi-asserted-by":"publisher","first-page":"1635","DOI":"10.1007\/s00034-020-01554-z","volume":"40","author":"Y Pu","year":"2021","unstructured":"Y. Pu, Y.Q. Yang, J. Chen, Some stochastic gradient algorithms for Hammerstein systems with piecewise linearity. Circuits Syst. Signal Process. 40(4), 1635\u20131651 (2021)","journal-title":"Circuits Syst. Signal Process."},{"key":"2116_CR29","doi-asserted-by":"publisher","DOI":"10.1016\/j.automatica.2021.109672","volume":"129","author":"H Reza","year":"2021","unstructured":"H. Reza, F. Mohammad, Robust tube-based model predictive control of LPV systems subject to adjustable additive disturbance set. Automatica 129, 109672 (2021)","journal-title":"Automatica"},{"issue":"25","key":"2116_CR30","doi-asserted-by":"publisher","first-page":"8678","DOI":"10.1021\/ie0601753","volume":"45","author":"R Senthil","year":"2006","unstructured":"R. Senthil, K. Janarthanan, J. Prakash, Nonlinear state estimation using fuzzy Kalman filter. Ind. Eng. Chem. Res. 45(25), 8678\u20138688 (2006)","journal-title":"Ind. Eng. Chem. Res."},{"issue":"2","key":"2116_CR31","doi-asserted-by":"publisher","first-page":"559","DOI":"10.1016\/0005-1098(91)90116-J","volume":"40","author":"JS Shamma","year":"1991","unstructured":"J.S. Shamma, M. Athans, Guaranteed properties of gain scheduled control for linear parameter-varying plants. Automatica 40(2), 559\u2013564 (1991)","journal-title":"Automatica"},{"key":"2116_CR32","doi-asserted-by":"crossref","unstructured":"W.L. Shi, Y.S. Li, F. Albu, A norm penalized noise-free maximum correntropy criterion algorithm, in 2019 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), November 18\u201321, Lanzhou, China (2019), pp. 1717\u20131720","DOI":"10.1109\/APSIPAASC47483.2019.9023318"},{"issue":"3","key":"2116_CR33","doi-asserted-by":"publisher","first-page":"3395","DOI":"10.1007\/s00034-020-01628-y","volume":"40","author":"P Song","year":"2021","unstructured":"P. Song, H.Q. Zhao et al., Robust time-varying parameter proportionate affine-projection-like algorithm for sparse system identification. Circuits Syst. Signal Process. 40(3), 3395\u20133416 (2021)","journal-title":"Circuits Syst. Signal Process."},{"issue":"1","key":"2116_CR34","first-page":"139","volume":"20","author":"R T\u00f3th","year":"2012","unstructured":"R. T\u00f3th, H.S. Abbas, H. Werner, Robust model predictive controller using recurrent neural networks for input\u2013output linear parameter-varying systems. IET Control Theory Appl. 20(1), 139\u2013153 (2012)","journal-title":"IET Control Theory Appl."},{"key":"2116_CR35","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2440-0","volume-title":"The Nature of Statistical Learning Theory","author":"V Vapnik","year":"1995","unstructured":"V. Vapnik, The Nature of Statistical Learning Theory (Springer, New York, 1995)"},{"issue":"2","key":"2116_CR36","doi-asserted-by":"publisher","first-page":"830","DOI":"10.1002\/rnc.5850","volume":"32","author":"XH Wang","year":"2022","unstructured":"X.H. Wang, F. Ding, Modified particle filtering-based robust estimation for a networked control system corrupted by impulsive noise. Int. J. Robust Nonlinear Control 32(2), 830\u2013850 (2022)","journal-title":"Int. J. Robust Nonlinear Control"},{"issue":"7","key":"2116_CR37","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1049\/cth2.12097","volume":"15","author":"XH Wang","year":"2021","unstructured":"X.H. Wang, F. Ding, The robust multi-innovation estimation algorithm for Hammerstein non-linear systems with non-Gaussian noise. IET Control Theory Appl. 15(7), 989\u20131002 (2021)","journal-title":"IET Control Theory Appl."},{"issue":"9","key":"2116_CR38","doi-asserted-by":"publisher","first-page":"4297","DOI":"10.1007\/s00034-020-01378-x","volume":"39","author":"XH Wang","year":"2020","unstructured":"X.H. Wang, F. Zhu et al., Bias correction-based recursive estimation for dual-rate output-error systems with sampling noise. Circuits Syst. Signal Process. 39(9), 4297\u20134319 (2020)","journal-title":"Circuits Syst. Signal Process."},{"issue":"12","key":"2116_CR39","doi-asserted-by":"publisher","first-page":"3903","DOI":"10.1007\/s12555-020-0589-0","volume":"19","author":"XH Wang","year":"2021","unstructured":"X.H. Wang, F. Zhu, A novel filtering based recursive estimation algorithm for Box-Jenkins systems. Int. J. Control Autom. Syst. 19(12), 3903\u20133913 (2021)","journal-title":"Int. J. Control Autom. Syst."},{"issue":"8","key":"2116_CR40","doi-asserted-by":"publisher","first-page":"432","DOI":"10.3390\/e19080432","volume":"19","author":"YY Wang","year":"2017","unstructured":"Y.Y. Wang, Y.S. Li, F. Albu, R. Yang, Group-constrained maximum correntropy criterion algorithms for estimating sparse mix-noised channels. Entropy 19(8), 432 (2017)","journal-title":"Entropy"},{"key":"2116_CR41","doi-asserted-by":"publisher","first-page":"282","DOI":"10.1016\/j.automatica.2017.06.009","volume":"83","author":"S Wollnack","year":"2017","unstructured":"S. Wollnack, H.S. Abbas, R. T\u00f3th, H. Werner, Fixed-structure LPV-IO controllers: an implicit representation based approach. Automatica 83, 282\u2013289 (2017)","journal-title":"Automatica"},{"issue":"2","key":"2116_CR42","doi-asserted-by":"publisher","first-page":"805","DOI":"10.1007\/s00034-021-01801-x","volume":"41","author":"L Xu","year":"2022","unstructured":"L. Xu, Separable multi-innovation Newton iterative modeling algorithm for multi-frequency signals based on the sliding measurement window. Circuits Syst. Signal Process. 41(2), 805\u2013830 (2022)","journal-title":"Circuits Syst. Signal Process."},{"key":"2116_CR43","doi-asserted-by":"publisher","first-page":"947","DOI":"10.1109\/LSP.2022.3152108","volume":"29","author":"H Xu","year":"2022","unstructured":"H. Xu, F. Ding, B. Champagne, Joint parameter and time-delay estimation for a class of nonlinear time-series models. IEEE Signal Process. Lett. 29, 947\u2013951 (2022)","journal-title":"IEEE Signal Process. Lett."},{"key":"2116_CR44","first-page":"6501313","volume":"71","author":"L Xu","year":"2022","unstructured":"L. Xu, F. Ding, Q.M. Zhu, Separable synchronous multi-innovation gradient-based iterative signal modeling from on-line measurements. IEEE Trans. Instrum. Meas. 71, 6501313 (2022)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"2116_CR45","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.chemolab.2015.08.013","volume":"148","author":"XQ Yang","year":"2015","unstructured":"X.Q. Yang, B. Huang, Y.J. Zhao, Y.J. Lu et al., Generalized expectation-maximization approach to LPV process identification with randomly missing output data. Chemometr. Intell. Lab. Syst. 148, 1\u20138 (2015)","journal-title":"Chemometr. Intell. Lab. Syst."},{"issue":"7","key":"2116_CR46","doi-asserted-by":"publisher","first-page":"1103","DOI":"10.1049\/iet-cta.2014.0694","volume":"9","author":"XQ Yang","year":"2015","unstructured":"X.Q. Yang, Y.J. Lu, Z.B. Yan, Robust global identification of linear parameter-varying systems with generalised expectation-maximisation algorithm. IET Control Theory Appl. 9(7), 1103\u20131110 (2015)","journal-title":"IET Control Theory Appl."},{"issue":"5","key":"2116_CR47","doi-asserted-by":"publisher","first-page":"2402","DOI":"10.1109\/TIE.2013.2273477","volume":"61","author":"S Yin","year":"2014","unstructured":"S. Yin, H. Luo, S.X. Ding, Real-time implementation of fault tolerant control systems with performance optimization. IEEE Trans. Ind. Electron. 61(5), 2402\u20132411 (2014)","journal-title":"IEEE Trans. Ind. Electron."},{"issue":"12","key":"2116_CR48","doi-asserted-by":"publisher","first-page":"1704","DOI":"10.1049\/iet-cta.2018.0156","volume":"12","author":"X Zhang","year":"2018","unstructured":"X. Zhang, F. Ding et al., State filtering-based least squares parameter estimation for bilinear systems using the hierarchical identification principle. IET Control Theory Appl. 12(12), 1704\u20131713 (2018)","journal-title":"IET Control Theory Appl."},{"key":"2116_CR49","doi-asserted-by":"publisher","first-page":"399","DOI":"10.1109\/LSP.2021.3136504","volume":"29","author":"X Zhang","year":"2022","unstructured":"X. Zhang, F. Ding, Optimal adaptive filtering algorithm by using the fractional-order derivative. IEEE Signal Process. Lett. 29, 399\u2013403 (2022)","journal-title":"IEEE Signal Process. Lett."},{"issue":"12","key":"2116_CR50","doi-asserted-by":"publisher","first-page":"3597","DOI":"10.1109\/TCSII.2021.3076112","volume":"68","author":"YH Zhou","year":"2021","unstructured":"Y.H. Zhou, F. Ding, Hierarchical estimation approach for RBF-AR models with regression weights based on the increasing data length. IEEE Trans. Circuits Syst. II 68(12), 3597\u20133601 (2021)","journal-title":"IEEE Trans. Circuits Syst. II"},{"key":"2116_CR51","volume":"414","author":"YH Zhou","year":"2022","unstructured":"Y.H. Zhou, X. Zhang et al., Partially-coupled nonlinear parameter optimization algorithm for a class of multivariate hybrid models. Appl. Math. Comput. 414, 126663 (2022)","journal-title":"Appl. Math. Comput."}],"container-title":["Circuits, Systems, and Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-022-02116-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00034-022-02116-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00034-022-02116-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,10,21]],"date-time":"2022-10-21T02:20:53Z","timestamp":1666318853000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00034-022-02116-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,7,22]]},"references-count":51,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,12]]}},"alternative-id":["2116"],"URL":"https:\/\/doi.org\/10.1007\/s00034-022-02116-1","relation":{},"ISSN":["0278-081X","1531-5878"],"issn-type":[{"type":"print","value":"0278-081X"},{"type":"electronic","value":"1531-5878"}],"subject":[],"published":{"date-parts":[[2022,7,22]]},"assertion":[{"value":"1 September 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 July 2022","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 July 2022","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 July 2022","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 potential conflict of interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}