{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T19:15:53Z","timestamp":1725909353006},"publisher-location":"Singapore","reference-count":15,"publisher":"Springer Singapore","isbn-type":[{"type":"print","value":"9789811063695"},{"type":"electronic","value":"9789811063701"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[[2017]]},"DOI":"10.1007\/978-981-10-6370-1_43","type":"book-chapter","created":{"date-parts":[[2017,8,24]],"date-time":"2017-08-24T08:12:34Z","timestamp":1503562354000},"page":"432-441","source":"Crossref","is-referenced-by-count":0,"title":["Identification Approach of Hammerstein-Wiener Model Corrupted by Colored Process Noise"],"prefix":"10.1007","author":[{"given":"Feng","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Jia","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qi","family":"Xiong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2017,8,25]]},"reference":[{"issue":"4","key":"43_CR1","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/j.automatica.2003.11.007","volume":"40","author":"EW Bai","year":"2004","unstructured":"Bai, E.W.: Decoupling the linear and nonlinear parts in Hammerstein model identification. Automatica 40(4), 671\u2013676 (2004)","journal-title":"Automatica"},{"issue":"9","key":"43_CR2","doi-asserted-by":"crossref","first-page":"2174","DOI":"10.1109\/TAC.2009.2026832","volume":"54","author":"F Giri","year":"2009","unstructured":"Giri, F., Rochdi, Y., Chaoui, F.Z.: Hammerstein systems identification in presence of hard nonlinearities of preload and dead-zone type. IEEE Trans. Autom. Control 54(9), 2174\u20132178 (2009)","journal-title":"IEEE Trans. Autom. Control"},{"issue":"11","key":"43_CR3","doi-asserted-by":"crossref","first-page":"2697","DOI":"10.1016\/j.automatica.2008.02.016","volume":"44","author":"A Hagenblad","year":"2008","unstructured":"Hagenblad, A., Ljung, L., Wills, A.: Maximum likelihood identification of Wiener models. Automatica 44(11), 2697\u20132705 (2008)","journal-title":"Automatica"},{"issue":"5","key":"43_CR4","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1016\/j.sigpro.2010.11.004","volume":"91","author":"DQ Wang","year":"2011","unstructured":"Wang, D.Q., Ding, F.: Least squares based and gradient based iterative identification for Wiener nonlinear systems. Signal Process. 91(5), 1182\u20131189 (2011)","journal-title":"Signal Process."},{"issue":"3","key":"43_CR5","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/S0005-1098(97)00198-2","volume":"34","author":"EW Bai","year":"1998","unstructured":"Bai, E.W.: An optimal two-stage identification algorithm for Hammerstein-Wiener nonlinear systems. Automatica 34(3), 333\u2013338 (1998)","journal-title":"Automatica"},{"issue":"6","key":"43_CR6","doi-asserted-by":"crossref","first-page":"967","DOI":"10.1016\/S0005-1098(01)00292-8","volume":"38","author":"EW Bai","year":"2002","unstructured":"Bai, E.W.: A blind approach to the Hammerstein-Wiener model identification. Automatica 38(6), 967\u2013979 (2002)","journal-title":"Automatica"},{"issue":"8","key":"43_CR7","doi-asserted-by":"crossref","first-page":"1108","DOI":"10.1016\/j.jprocont.2013.06.014","volume":"23","author":"F Yu","year":"2013","unstructured":"Yu, F., Mao, Z.Z., Jia, M.X.: Recursive identification for Hammerstein-Wiener systems with dead-zone input nonlinearity. J. Proc. Control 23(8), 1108\u20131115 (2013)","journal-title":"J. Proc. Control"},{"issue":"2","key":"43_CR8","doi-asserted-by":"crossref","first-page":"825","DOI":"10.1109\/LSP.2012.2221704","volume":"19","author":"DQ Wang","year":"2012","unstructured":"Wang, D.Q., Ding, F.: Hierarchical least squares estimation algorithm for Hammerstein-Wiener systems. IEEE Signal Proc. Let 19(2), 825\u2013828 (2012)","journal-title":"IEEE Signal Proc. Let"},{"issue":"1","key":"43_CR9","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1080\/00207721.2015.1036478","volume":"47","author":"B Zhang","year":"2015","unstructured":"Zhang, B., Mao, Z.Z.: Adaptive control of stochastic Hammerstein-Wiener nonlinear systems with measurement noise. Int. J. Syst. Sci. 47(1), 162\u2013178 (2015)","journal-title":"Int. J. Syst. Sci."},{"issue":"9","key":"43_CR10","doi-asserted-by":"crossref","first-page":"1276","DOI":"10.1049\/iet-cta.2012.0548","volume":"7","author":"B Ni","year":"2013","unstructured":"Ni, B., Gilson, M., Garnier, H.: Refined instrumental variable method for Hammerstein-Wiener continuous-time model identification. IET Contr. Theor. Appl. 7(9), 1276\u20131286 (2013)","journal-title":"IET Contr. Theor. Appl."},{"issue":"3","key":"43_CR11","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1016\/j.neucom.2012.01.039","volume":"94","author":"M Salimifard","year":"2012","unstructured":"Salimifard, M., Jafari, M., Dehghani, M.: Identification of nonlinear MIMO block-oriented systems with moving average noises using gradient based and least squares based iterative algorithms. Neurocomputing 94(3), 22\u201331 (2012)","journal-title":"Neurocomputing"},{"issue":"8","key":"43_CR12","first-page":"90","volume":"244","author":"F Li","year":"2017","unstructured":"Li, F., Jia, L., Peng, D.G., Han, C.: Neuro-fuzzy based identification method for Hammerstein output error model with colored noise. Neurocomputing 244(8), 90\u2013101 (2017)","journal-title":"Neurocomputing"},{"key":"43_CR13","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1016\/j.neucom.2015.06.089","volume":"174","author":"L Jia","year":"2016","unstructured":"Jia, L., Li, X.L., Chiu, M.S.: The identification of neuro-fuzzy based MIMO Hammerstein model with separable input signals. Neurocomputing 174, 530\u2013541 (2016)","journal-title":"Neurocomputing"},{"issue":"7","key":"43_CR14","first-page":"400","volume":"11","author":"SS Hu","year":"1990","unstructured":"Hu, S.S.: Identification of parameters of MIMO systems by correlation analysis. Acta Aeronaut. et Astronaut. Sin. 11(7), 400\u2013404 (1990)","journal-title":"Acta Aeronaut. et Astronaut. Sin."},{"issue":"7","key":"43_CR15","doi-asserted-by":"crossref","first-page":"749","DOI":"10.1016\/j.jprocont.2005.03.006","volume":"15","author":"L Jia","year":"2005","unstructured":"Jia, L., Chiu, M.S., Ge, S.S.: A noniterative neuro-fuzzy based identification method for Hammerstein processes. J. Proc. Control 15(7), 749\u2013761 (2005)","journal-title":"J. Proc. Control"}],"container-title":["Communications in Computer and Information Science","Advanced Computational Methods in Life System Modeling and Simulation"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-10-6370-1_43","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2017,8,24]],"date-time":"2017-08-24T08:21:17Z","timestamp":1503562877000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-981-10-6370-1_43"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9789811063695","9789811063701"],"references-count":15,"URL":"https:\/\/doi.org\/10.1007\/978-981-10-6370-1_43","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2017]]}}}