Fixed-time synchronization of fuzzy inertial neural networks based on non-reduced order approach
CHEN Teng
DAI Hou-ping
LONG Chang-qing
Abstract：Up to now,the fixed-time synchronization analysis of inertial neural networks has mainly utilized variable substitution method,which is effective,but expands the system's dimension and eliminates the influence of the inertial term.In order to consider the intuitive effects of the inertia term,this paper discusses the fixed-time synchronization of delayed fuzzy neural networks with inertia terms via using the non-reduced-order approach.Under the Filippov solution framework and finite time stability theory,some synchronization criteria are obtained to ensure the realization of fixed-time synchronization of the proposed neural system by designing nonlinear feedback controller.In addition,the upper bound of the synchronization time is estimated by using some inequality techniques,which can provide reliability guarantee for its application in practical engineering.Finally,the results obtained in this article are verified through numerical examples and an image encryption application.
Keywords：discontinuous activationfuzzy inertial neural networksfixed-time synchronizationnon-reduced order approach
Publication Date：2025-10-30
Online Publishing Date：2025-11-13(First online date of this platform, not the publication date of the document)
Pages：9( 1990-1998 )