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The Effect of Caputo Fractional Variable Difference Operator on a Discrete-Time Hopfield Neural Network with Non-Commensurate Order.
- Source :
- Fractal & Fractional; Oct2022, Vol. 6 Issue 10, pN.PAG-N.PAG, 13p
- Publication Year :
- 2022
-
Abstract
- In this work, we recall some definitions on fractional calculus with discrete-time. Then, we introduce a discrete-time Hopfield neural network (D.T.H.N.N) with non-commensurate fractional variable-order (V.O) for three neurons. After that, phase-plot portraits, bifurcation and Lyapunov exponents diagrams are employed to verify that the proposed discrete time Hopfield neural network with non-commensurate fractional variable order has chaotic behavior. Furthermore, we use the 0-1 test and C 0 complexity algorithm to confirm and prove the results obtained about the presence of chaos. Finally, simulations are carried out in Matlab to illustrate the results. [ABSTRACT FROM AUTHOR]
- Subjects :
- HOPFIELD networks
DIFFERENCE operators
LYAPUNOV exponents
FRACTIONAL calculus
Subjects
Details
- Language :
- English
- ISSN :
- 25043110
- Volume :
- 6
- Issue :
- 10
- Database :
- Complementary Index
- Journal :
- Fractal & Fractional
- Publication Type :
- Academic Journal
- Accession number :
- 159871859
- Full Text :
- https://doi.org/10.3390/fractalfract6100575