scholarly journals A Neural Network Approach for Solving Fractional-Order Model of HIV Infection of CD4+T-Cells

2016 ◽  
Vol 2 (06) ◽  
pp. 65-69 ◽  
Author(s):  
Samaneh Soradi Zeid
Keyword(s):  
Neural Network ◽  
T Cells ◽  
Hiv Infection ◽  
Fractional Order ◽  
Cd4 T Cells ◽  
Network Approach ◽  
Order Model ◽  
Neural Network Approach ◽  
Fractional Order Model

scholarly journals Solving a fractional order model of HIV infection of CD4+ T cells

2011 ◽  
Vol 54 (9-10) ◽  
pp. 2132-2138 ◽  
Author(s):  
Ahmet Gökdoǧan ◽  
Ahmet Yildirim ◽  
Mehmet Merdan
Keyword(s):  
T Cells ◽  
Hiv Infection ◽  
Fractional Order ◽  
Cd4 T Cells ◽  
Order Model ◽  
Fractional Order Model

scholarly journals An impulsive delay discrete stochastic neural network fractional-order model and applications in finance

Filomat ◽  
2018 ◽  
Vol 32 (18) ◽  
pp. 6339-6352
Author(s):  
Martin Bohner ◽  
Ivanka Stamova
Keyword(s):  
Neural Network ◽  
Fractional Order ◽  
Financial Assets ◽  
Order Model ◽  
Stochastic Neural Network ◽  
Modeling And Analysis ◽  
Fractional Order Model ◽  
Noise Disturbances ◽  
Impulsive Delay ◽  
Stochastic Term

In this paper, we propose a new tool for modeling and analysis in finance, introducing an impulsive discrete stochastic neural network (NN) fractional-order model. The main advantages of the proposed approach are: (i) Using NNs which can be trained without the restriction of a model to derive parameters and discover relationships, driven and shaped solely by the nature of the data; (ii) using fractional-order differences, whose nonlocal property makes the fractional calculus a suitable tool for modeling actual financial systems; (iii) using impulsive perturbations, which give an opportunity to control the dynamic behavior of the model; (iv) including a stochastic term, which allows to study the effect of noise disturbances generally existing in financial assets; (v) taking into account the existence of time delayed influences. The modeling approach proposed in this paper can be applied to investigate macroeconomic systems.

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