Abstract
This paper is concerned with the L∞ performance analysis problem for time-varying delayed neural networks. First, a condition is proposed for the L∞ performance of single neural networks with time-varying delay and persistent bounded input based on the Wirtinger-type inequality together with the reciprocal convex approach. Then, sufficient conditions are established to ensure the L∞ performance of interconnected neural networks with time-varying delay. Numerical examples are provided to show the effectiveness of the presented results.
Original language | English |
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Pages (from-to) | 412-423 |
Number of pages | 12 |
Journal | Information Sciences |
Volume | 346-347 |
DOIs | |
Publication status | Published - 2016 Jun 10 |
Bibliographical note
Funding Information:This work was partially supported by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (NRF-2014R1A1A1006101) and partially by “Human Resources program in Energy Technology” of the Korea Institute of Energy Technology Evaluation and Planning (KETEP) granted financial resource from the Ministry of Trade, Industry & Energy, Republic of Korea (No. 20154030200610).
Publisher Copyright:
© 2016 Elsevier Inc.
Copyright:
Copyright 2018 Elsevier B.V., All rights reserved.
Keywords
- Feedback interconnection
- L performance
- Neural network
- Time-varying delay
ASJC Scopus subject areas
- Software
- Control and Systems Engineering
- Theoretical Computer Science
- Computer Science Applications
- Information Systems and Management
- Artificial Intelligence