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Distinct from the frequently employed reduced-order technique, this paper studies SINN directly through non-reduced order method. By constructing a novel Lyapunov functional and using Barbalat Lemma, sufficient conditions for the global asymptotic stabilization issue and global exponential stabilization issue of the considered SINN are established. Numerical simulations further confirm the feasibility of the main results. The comparative research shows that global stabilization results of this paper complement and improve some existing work.<\/jats:p>","DOI":"10.1177\/0142331220985944","type":"journal-article","created":{"date-parts":[[2021,1,18]],"date-time":"2021-01-18T04:43:02Z","timestamp":1610944982000},"page":"1949-1957","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":7,"title":["Stabilization for a class of delayed switched inertial neural networks via non-reduced order method"],"prefix":"10.1177","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3797-3282","authenticated-orcid":false,"given":"Xuan","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Automation, Xiamen University, China"},{"name":"School of Physics and Electronic Science, Guizhou Normal University, 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