Journal
IEEE TRANSACTIONS ON CYBERNETICS
Volume 51, Issue 1, Pages 151-161Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TCYB.2020.2967625
Keywords
Delays; Neural networks; Mathematical model; Perturbation methods; Stability criteria; Almost periodic processes; fractional derivatives; impulsive control; neural networks; reaction– diffusion terms; stability; time-varying delays; uncertain terms
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Funding
- National Natural Science Foundation of China [61573096, 61833005]
- Jiangsu Provincial Key Laboratory of Networked Collective Intelligence [BM2017002]
- European Regional Development Fund through the Operational Programme Science and Education for Smart Growth [UNITe BG05M2OP001-1.001-0004]
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This article investigates a neural-network model of fractional order with impulsive perturbations, time-varying delays, and reaction-diffusion terms, focusing on qualitative properties of states and developing new almost periodicity and stability criteria. The uncertain case is also considered, and examples are established to demonstrate the effectiveness of the obtained criteria.
A neural-network model of fractional order with impulsive perturbations, time-varying delays, and reaction-diffusion terms is investigated in this article. The focus is on investigating qualitative properties of the states and developing new almost periodicity and stability criteria. The uncertain case is also considered. Examples are established and the effectiveness of the obtained criteria is demonstrated.
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