Analog and digital implementation of fractional-order FitzHugh–Nagumo (FO-FHN) neuron model

2022 ◽  
pp. 475-504
Author(s):  
Mohammad Rafiq Dar ◽  
Nasir Ali Kant ◽  
Farooq Ahmad Khanday ◽  
Shakeel Ahmad Malik ◽  
Mubashir Ahmad Kharadi
Inventions ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 49
Author(s):  
Zain-Aldeen S. A. Rahman ◽  
Basil H. Jasim ◽  
Yasir I. A. Al-Yasir ◽  
Raed A. Abd-Alhameed ◽  
Bilal Naji Alhasnawi

In this paper, a new fractional order chaotic system without equilibrium is proposed, analytically and numerically investigated, and numerically and experimentally tested. The analytical and numerical investigations were used to describe the system’s dynamical behaviors including the system equilibria, the chaotic attractors, the bifurcation diagrams, and the Lyapunov exponents. Based on the obtained dynamical behaviors, the system can excite hidden chaotic attractors since it has no equilibrium. Then, a synchronization mechanism based on the adaptive control theory was developed between two identical new systems (master and slave). The adaptive control laws are derived based on synchronization error dynamics of the state variables for the master and slave. Consequently, the update laws of the slave parameters are obtained, where the slave parameters are assumed to be uncertain and are estimated corresponding to the master parameters by the synchronization process. Furthermore, Arduino Due boards were used to implement the proposed system in order to demonstrate its practicality in real-world applications. The simulation experimental results were obtained by MATLAB and the Arduino Due boards, respectively, with a good consistency between the simulation results and the experimental results, indicating that the new fractional order chaotic system is capable of being employed in real-world applications.


2018 ◽  
Vol 12 (1) ◽  
pp. 47-57 ◽  
Author(s):  
Elahe Rahimian ◽  
Soheil Zabihi ◽  
Mahmood Amiri ◽  
Bernabe Linares-Barranco

2019 ◽  
Vol 30 (7) ◽  
pp. 2108-2122 ◽  
Author(s):  
Farooq Ahmad Khanday ◽  
Nasir Ali Kant ◽  
Mohammad Rafiq Dar ◽  
Tun Zainal Azni Zulkifli ◽  
Costas Psychalinos

2017 ◽  
Vol 23 (1) ◽  
pp. 10-14 ◽  
Author(s):  
Timothée Levi ◽  
Farad Khoyratee ◽  
Sylvain Saïghi ◽  
Yoshiho Ikeuchi

Author(s):  
M. A. Bañuelos-Saucedo ◽  
J. Castillo-Hernández ◽  
S. Quintana-Thierry ◽  
R. Damián-Zamacona ◽  
J. Valeriano-Assem ◽  
...  

Artificial neural networks base their processing capabilities in a parallel architecture, and this makes them useful to solve pattern recognition, system identification, and control problems. In this paper, we present a FPGA (Field Programmable Gate Array) based digital implementation of a McCulloch-Pitts type of neuron model with three types of non-linear activation function: step, ramp-saturation, and sigmoid. We present the VHDL language code used to implement the neurons as well as to present simulation results obtained with Xilinx Foundation 3.0 software. The results are analyzed in terms of speed and percentage of chip usage.


Author(s):  
Esteban Tlelo-Cuautle ◽  
Ana Dalia Pano-Azucena ◽  
Omar Guillén-Fernández ◽  
Alejandro Silva-Juárez

2021 ◽  
Vol 94 (12) ◽  
Author(s):  
Noel Freddy Fotie Foka ◽  
Balamurali Ramakrishnan ◽  
André Rodrigue Tchamda ◽  
Sifeu Takougang Kingni ◽  
Karthikeyan Rajagopal ◽  
...  

2018 ◽  
Vol 12 (6) ◽  
pp. 696-706 ◽  
Author(s):  
Farooq Ahmad Khanday ◽  
Mohammad Rafiq Dar ◽  
Nasir Ali Kant ◽  
Josep L. Rossello ◽  
Costas Psychalinos

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