{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T04:16:50Z","timestamp":1760242610029,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2017,12,23]],"date-time":"2017-12-23T00:00:00Z","timestamp":1513987200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61374180","61373136"],"award-info":[{"award-number":["61374180","61373136"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>Estimating uncertain state variables of a general complex dynamical network with randomly incomplete measurements of transmitted output variables is investigated in this paper. The incomplete measurements, occurring randomly through the transmission of output variables, always cause the failure of the state estimation process. Different from the existing methods, we propose a novel method to handle the incomplete measurements, which can perform well to balance the excessively deviated estimators under the influence of incomplete measurements. In particular, the proposed method has no special limitation on the node dynamics compared with many existing methods. By employing the Lyapunov stability theory along with the stochastic analysis method, sufficient criteria are deduced rigorously to ensure obtaining the proper estimator gains with known model parameters. Illustrative simulation for the complex dynamical network composed of chaotic nodes are given to show the validity and efficiency of the proposed method.<\/jats:p>","DOI":"10.3390\/e20010005","type":"journal-article","created":{"date-parts":[[2017,12,26]],"date-time":"2017-12-26T03:06:38Z","timestamp":1514257598000},"page":"5","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["State Estimation for General Complex Dynamical Networks with Incompletely Measured Information"],"prefix":"10.3390","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6952-7650","authenticated-orcid":false,"given":"Xinwei","family":"Wang","sequence":"first","affiliation":[{"name":"College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guo-Ping","family":"Jiang","sequence":"additional","affiliation":[{"name":"College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Wu","sequence":"additional","affiliation":[{"name":"College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,12,23]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1038\/35065725","article-title":"Exploring complex networks","volume":"410","author":"Strogatz","year":"2001","journal-title":"Nature"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"440","DOI":"10.1038\/30918","article-title":"Collective dynamics of \u2018small-world\u2019 networks","volume":"393","author":"Watts","year":"1998","journal-title":"Nature"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1126\/science.286.5439.509","article-title":"Emergence of scaling in random networks","volume":"286","author":"Albert","year":"1999","journal-title":"Science"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"4932","DOI":"10.3390\/e15114932","article-title":"Dynamical structure of a traditional Amazonian social network","volume":"15","author":"Hooper","year":"2013","journal-title":"Entropy"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"74","DOI":"10.3390\/e17010074","article-title":"Entropy-based characterization of Internet background radiation","volume":"17","author":"Iglesias","year":"2014","journal-title":"Entropy"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Nandi, A., Kafashan, M.M., and Ching, S.N. 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