Akademik Veri Yönetim Sistemi
PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, sa.3, ss.316-323, 2024 (ESCI)
The biological neuron models, which have the biologically significant, describe the characteristics of neurons in the living body. These models can be defined similar to oscillators. A great of the theorems that describe the characteristics of oscillator structures, such as stability control and synchronization control, can also be used to examine the biological neuron models. Recently, the rotation -transition process has become a remarkable issue in the nonlinear dynamical system applications. After the rotation -transition process; the dynamical attractor of a nonlinear system can be directed to any desired direction by changing the rotation angle. One of the most known examples of the nonlinear dynamical systems is the chaotic oscillator structures. There are many studies on the dynamical attractor control of the chaotic oscillators by means of rotation -transition in the literature. However; although the rotation changes are observed in the dynamical characteristics of the real biological systems, there isn't any study dealing with the rotation controls of the dynamical attractors of biological neuron models. Therefore, the rotation -transition procedure of the Fitzhugh-Nagumo (FHN) model has been handled in this study. The equilibrium points of the rotated FHN neuron model are calculated for getting its characteristic outputs. After the rotation -transition process, the changes on the rotation of the dynamic attractors of the FHN neuron have been observed by numerical simulation results. Finally, the rotated -controlled FHN neuron has also been realized with the 'Field Programmable Gate Array- (FPGA)', which is a programmable and reconfigurable device, in order to both support the functionality of the rotation transformation process and to obtain the real-time signals requiring for the bio-inspired systems. Thus, it has been shown that thanks to the proposed rotation -transition process, the phase adjustment of the system dynamics in neural systems can be intervened without requiring any coupling definition. Based on this view; the mathematical descriptions of the rotated-FHN neuron model has been pointed out, this model is promoted by the numerical simulations and confirmed by the hardware implementation studies.