Global stability of Clifford-valued Takagi-Sugeno fuzzy neural networks with time-varying delays and impulses

Sriraman, Ramalingam ; Nedunchezhiyan, Asha

Kybernetika, Tome 58 (2022) no. 4, pp. 498-521

Abstract (VO)

In this study, we consider the Takagi-Sugeno (T-S) fuzzy model to examine the global asymptotic stability of Clifford-valued neural networks with time-varying delays and impulses. In order to achieve the global asymptotic stability criteria, we design a general network model that includes quaternion-, complex-, and real-valued networks as special cases. First, we decompose the $n$-dimensional Clifford-valued neural network into $2^mn$-dimensional real-valued counterparts in order to solve the noncommutativity of Clifford numbers multiplication. Then, we prove the new global asymptotic stability criteria by constructing an appropriate Lyapunov-Krasovskii functionals (LKFs) and employing Jensen's integral inequality together with the reciprocal convex combination method. All the results are proven using linear matrix inequalities (LMIs). Finally, a numerical example is provided to show the effectiveness of the achieved results.

Détail

DOI : 10.14736/kyb-2022-4-0498

Classification : 03E72, 34D08, 35R12, 92B20
Keywords: global stability; T-S fuzzy; Clifford-valued neural networks; Lyapunov--Krasovskii functionals; impulses

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