Extended dissipativity criterion for fractional-order neural networks with time-varying parameter and interval uncertainties

This paper investigates the issue of extended dissipativity performance for a class of fractional-order uncertain neural networks. Distinct from the earlier studies, the main purpose of focusing on this problem is to answer the question of extending the extended dissipative concept to the fractional...

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Bibliographic Details
Published in:Computational & applied mathematics 2022-04, Vol.41 (3), Article 95
Main Authors: Shafiya, M., Nagamani, G.
Format: Article
Language:English
Subjects:
Applications of Mathematics
Applied physics
Computational mathematics
Computational Mathematics and Numerical Analysis
Linear matrix inequalities
Mathematical analysis
Mathematical Applications in Computer Science
Mathematical Applications in the Physical Sciences
Mathematics
Mathematics and Statistics
Neural networks
Parameter uncertainty
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Summary:This paper investigates the issue of extended dissipativity performance for a class of fractional-order uncertain neural networks. Distinct from the earlier studies, the main purpose of focusing on this problem is to answer the question of extending the extended dissipative concept to the fractional-order uncertain neural networks, and this purpose has been successfully achieved by providing some sufficient conditions. By utilizing the concept of Lyapunov stability theory and linear matrix inequality techniques, some sufficient criteria have been derived to ensure the extended dissipativity performance of the considered class of fractional-order neural networks with two types of uncertainties, namely, time-varying parameter uncertainties and interval uncertainties. These obtained results also generalize those in integer-order cases. The concept of the extended dissipativity can be used to specify the L 2 - L ∞ performance, H ∞ performance, passivity performance, and ( Ψ 1 , Ψ 2 , Ψ 3 ) -dissipativity by adjusting the weighting matrices with appropriate performance level. Examples are provided to show the effectiveness and less conservatism of the proposed technique.
ISSN:2238-3603
1807-0302
DOI:10.1007/s40314-022-01799-1