Finite-time synchronisation for fuzzy inertial neural networks via an innovative approach
Huilan Wang, Zhengqiu Zhang · International Journal of Systems Science · 2025
In this study, the issue of the finite-time synchronisation (FTSN) for drive-response fuzzy inertial neural networks (DRFINNS) is discussed. Without applying the existing methods, such as the linear matrix inequality (LMI) method, finite-time stability theorems (FTST), integral inequality approach, the maximum-valued approach (MVM), using the Laplace transform approach (LTA) and inequality techniques, two novel criteria are derived for guaranteeing the FTSN for the considered DRFINNS. Using the LTA with inequal skills investigates the FTSN of DRFINNS is an innovative work.