Robust stability criteria for Takagi–Sugeno fuzzy Cohen–Grossberg neural networks of neutral type

The aim of this paper is to analyze the robust stability problem of Takagi–Sugeno fuzzy Cohen–Grossberg neural networks of neutral type. By constructing a Lyapunov–Krasovskii functional, which contains some triple and quadruple integral terms, and using a vector Wirtinger-type inequality approach, a delay dependent criterion is obtained to guarantee the stability of the addressed system. These conditions are expressed in terms of linear matrix inequalities that can be easily facilitated by using some standard numerical packages. Finally, numerical examples are given to illustrate the strength of the proposed method.