Enhanced bifurcation results for a delayed fractional neural network with heterogeneous orders-Reference-Cited by-同舟云学术

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Enhanced bifurcation results for a delayed fractional neural network with heterogeneous orders

Published:2019-07 Issue: Volume:526 Page:121014
ISSN:0378-4371
Container-title:Physica A: Statistical Mechanics and its Applications
language:en
Short-container-title:Physica A: Statistical Mechanics and its Applications

Author:

Huang Chengdai,Tang Jingyong,Niu Yantao,Cao Jinde

Funder

Nanhu Scholars Program for Young Scholars of Xinyang Normal University

Hubei Provincial Department of Education

Publisher

Elsevier BV

Subject

Condensed Matter Physics,Statistics and Probability

Reference32 articles.

1. Global exponential stability and dissipativity of generalized neural networks with time-varying delay signals;Manivannan;Neural Netw.,2017

2. Y.J. Fan, X. Huang, Y.X. Li, J.W. Xia, G.R. Chen, Aperiodically intermittent control for quasi-synchronization of delayed memristive neural networks: an interval matrix and matrix measure combined method, IEEE Transactions on Systems, Man, and Cybernetics: Systems, http://dx.doi.org/10.1109/TSMC.2018.2850157.

3. Globally robust stability analysis for stochastic Cohen-Grossberg neural networks with impulse control and time-varying delays;Guo;UKR. Math. J.,2018

4. Mean square exponential stability of stochastic delay cellular neural networks;Guo;Electron. J. Qual. Theory Differ. Equ.,2013

5. Global stability analysis for a class of Cohen–Grossberg neural network models;Guo;Bull. Korean Math. Soc.,2012

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