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

Title:

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

Creator:

Sriraman, Ramalingam and Nedunchezhian, Asha

Identifier:

https://cdk.lib.cas.cz/client/handle/uuid:b438d66c-a82c-4fd2-959d-bd9497726962
uuid:b438d66c-a82c-4fd2-959d-bd9497726962
doi:10.14736/kyb-2022-4-0498

Subject:

global stability, T-S fuzzy, Clifford-valued neural networks, Lyapunov-Krasovskii functionals, and impulses

Type:

model:article and TEXT

Format:

bez média and svazek

Description:

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 2mn-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.

Language:

English

Rights:

http://creativecommons.org/licenses/by-nc-sa/4.0/
policy:public

Coverage:

498-521

Source:

Kybernetika | 2022 Volume:58 | Number:4

Harvested from:

CDK

Metadata only:

false