{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T17:42:06Z","timestamp":1754156526464,"version":"3.41.2"},"reference-count":42,"publisher":"Emerald","issue":"1","license":[{"start":{"date-parts":[[2019,2,28]],"date-time":"2019-02-28T00:00:00Z","timestamp":1551312000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.emerald.com\/insight\/site-policies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJICC"],"published-print":{"date-parts":[[2019,2,28]]},"abstract":"<jats:sec><jats:title content-type=\"abstract-subheading\">Purpose<\/jats:title><jats:p>The purpose of this paper is to develop a method for the existence, uniqueness and globally robust stability of the equilibrium point for Cohen\u2013Grossberg neural networks with time-varying delays, continuous distributed delays and a kind of discontinuous activation functions.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design\/methodology\/approach<\/jats:title><jats:p>Based on the Leray\u2013Schauder alternative theorem and chain rule, by using a novel integral inequality dealing with monotone non-decreasing function, the authors obtain a delay-dependent sufficient condition with less conservativeness for robust stability of considered neural networks.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings<\/jats:title><jats:p>It turns out that the authors\u2019 delay-dependent sufficient condition can be formed in terms of linear matrix inequalities conditions. Two examples show the effectiveness of the obtained results.<\/jats:p><\/jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title><jats:p>The novelty of the proposed approach lies in dealing with a new kind of discontinuous activation functions by using the Leray\u2013Schauder alternative theorem, chain rule and a novel integral inequality on monotone non-decreasing function.<\/jats:p><\/jats:sec>","DOI":"10.1108\/ijicc-08-2018-0105","type":"journal-article","created":{"date-parts":[[2019,1,16]],"date-time":"2019-01-16T06:25:17Z","timestamp":1547619917000},"page":"82-101","source":"Crossref","is-referenced-by-count":2,"title":["Robust stability of mixed Cohen\u2013Grossberg neural networks with discontinuous activation 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