L performance of single and interconnected neural networks with time-varying delay

Choon Ki Ahn, Peng Shi, Ramesh K. Agarwal, Jing Xu

    Research output: Contribution to journalArticlepeer-review

    37 Citations (Scopus)

    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 languageEnglish
    Pages (from-to)412-423
    Number of pages12
    JournalInformation Sciences
    Volume346-347
    DOIs
    Publication statusPublished - 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

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