{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T18:08:33Z","timestamp":1788804513597,"version":"build-2803163510"},"reference-count":32,"publisher":"L and H Scientific Publishing, LLC","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["DNC"],"published-print":{"date-parts":[[2027,3,1]]},"abstract":"<jats:p>This article delves into investigating the existence of solutions for fractional-order neural networks (FNN), alongside analyzing the finite-time stability (FTS) of fractional differential equations. FTS, which focuses on trajectories converging to equilibrium within a short time frame, is a central aspect of this exploration. Employing Gronwall's inequality as the primary analytical tool, the study derives conditions for FTS. The theoretical findings are then substantiated through rigorous numerical simulations.<\/jats:p>","DOI":"10.5890\/dnc.2027.03.007","type":"journal-article","created":{"date-parts":[[2026,9,7]],"date-time":"2026-09-07T17:41:02Z","timestamp":1788802862000},"page":"97-109","source":"Crossref","is-referenced-by-count":0,"title":["Existence and Finite-Time Stability Analysis of Fractional Neural Networks Using Gronwall's Inequality"],"prefix":"10.5890","volume":"16","author":[{"given":"K.","family":"Kaliraj","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"S. 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