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The main works are as follows: First, a neural network is introduced to approximate the uncertain nonlinear item of the systems. Second, the observer-based adaptive event-triggering (OB-AET) strategy is designed to efficiently utilize communication and computing resources. Furthermore, the closed-loop switched systems considering injection attacks are established. By utilizing the Lyapunov function method and average dwell time technique, sufficient conditions for the exponential stability of the closed-loop switched systems are given. Accordingly, the gains of the state feedback controllers and observers are solved. Finally, simulation examples are given to verify the effectiveness of the proposed method.<\/jats:p>","DOI":"10.1177\/01423312241235985","type":"journal-article","created":{"date-parts":[[2024,3,15]],"date-time":"2024-03-15T23:23:30Z","timestamp":1710545010000},"page":"2627-2635","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":3,"title":["Adaptive event-triggered control for neural network\u2013approximated switched systems under injection attacks"],"prefix":"10.1177","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7113-7114","authenticated-orcid":false,"given":"Yiwen","family":"Qi","sequence":"first","affiliation":[{"name":"School of Automation, Shenyang Aerospace University, China"},{"name":"College of Electrical Engineering and Automation, Fuzhou University, 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