Dissipativity Analysis for Neural Networks with Time-Varying Delays via a Delay-Product-Type Lyapunov Functional Approach

No Thumbnail Available
File version
Author(s)
Lian, HH
Xiao, SP
Yan, H
Yang, F
Zeng, HB
Griffith University Author(s)
Primary Supervisor
Other Supervisors
Editor(s)
Date
2021
Size
File type(s)
Location
License
Abstract

This article is concerned with the problem of dissipativity and stability analysis for a class of neural networks (NNs) with time-varying delays. First, a new augmented Lyapunov-Krasovskii functional (LKF), including some delay-product-type terms, is proposed, in which the information on time-varying delay and system states is taken into full consideration. Second, by employing a generalized free-matrix-based inequality and its simplified version to estimate the derivative of the proposed LKF, some improved delay-dependent conditions are derived to ensure that the considered NNs are strictly ( Q , S , R )- $\gamma $ -dissipative. Furthermore, the obtained results are applied to passivity and stability analysis of delayed NNs. Finally, two numerical examples and a real-world problem in the quadruple tank process are carried out to illustrate the effectiveness of the proposed method.

Journal Title

IEEE Transactions on Neural Networks and Learning Systems

Conference Title
Book Title
Edition
Volume

32

Issue

3

Thesis Type
Degree Program
School
Publisher link
Patent number
Funder(s)
Grant identifier(s)
Rights Statement
Rights Statement
Item Access Status
Note
Access the data
Related item(s)
Subject

Neural networks

Persistent link to this record
Citation

Lian, HH; Xiao, SP; Yan, H; Yang, F; Zeng, HB, Dissipativity Analysis for Neural Networks with Time-Varying Delays via a Delay-Product-Type Lyapunov Functional Approach, IEEE Transactions on Neural Networks and Learning Systems, 2021, 32 (3), pp. 975-984

Collections