Journal
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Volume 49, Issue 3, Pages 537-545Publisher
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207721.2017.1412534
Keywords
Asymptotic stability; Riemann-Liouville fractional neural networks; Lyapunov functional method; discrete and distributed delays
Categories
Funding
- National Natural Science Foundation of China [11301308, 11371027, 61573096, 61272530]
- Foundation of Jiangsu Provincial Key Laboratory of Networked Collective Intelligence [BM2017002]
- 333 Engineering Foundation of Jiangsu Province of China [BRA2015286]
- Natural Science Foundation of Anhui Province of China [1608085MA14]
- Key Project of Natural Science Research of Anhui Higher Education Institutions of China [gxyqZD2016205, KJ2015A152]
- Natural Science Youth Foundation of Jiangsu Province of China [BK20160660]
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This paper is concerned with the asymptotic stability of the Riemann-Liouville fractional-order neural networks with discrete and distributed delays. By constructing a suitable Lyapunov functional, two sufficient conditions are derived to ensure that the addressed neural network is asymptotically stable. The presented stability criteria are described in terms of the linear matrix inequalities. The advantage of the proposed method is that one may avoid calculating the fractional-order derivative of the Lyapunov functional. Finally, a numerical example is given to show the validity and feasibility of the theoretical results.
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