@article{0c47dbd1b3a4495dbb500664e520c81c,
title = "L∞ performance of single and interconnected neural networks with time-varying delay",
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.",
keywords = "Feedback interconnection, L performance, Neural network, Time-varying delay",
author = "Ahn, \{Choon Ki\} and Peng Shi and Agarwal, \{Ramesh K.\} and Jing Xu",
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: {\textcopyright} 2016 Elsevier Inc.",
year = "2016",
month = jun,
day = "10",
doi = "10.1016/j.ins.2016.02.004",
language = "English",
volume = "346-347",
pages = "412--423",
journal = "Information Sciences",
issn = "0020-0255",
}