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A new augmented vector with the derivative of the state is introduced in the Lyapunov\u2013Krasovskii functional. The state estimation criteria are obtained by constructing the suitable Lyapunov\u2013Krasovskii functional; meanwhile, the observer gain and the controller gain are derived in terms of linear matrix inequality. The free matrix\u2010based integral inequality is utilized to handle the integral terms, and the zero equation is added to the derivative of the Lyapunov\u2013Krasovskii functional, which decreases the conservatism. The effectiveness and feasibility of the proposed methods are demonstrated by two numerical examples.<\/jats:p>","DOI":"10.1155\/2022\/4618101","type":"journal-article","created":{"date-parts":[[2022,8,25]],"date-time":"2022-08-25T20:50:08Z","timestamp":1661460608000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["State Estimation for Standard Neural Network Models with Time\u2010Varying 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