Optimized Implement at ion of the Hodgkin-Huxley Model on FPGA Using 𝟐𝟐 Modules and Taylor Series Expansion for Enhanced Speed and Efficiency

The current research demonst rates that innovative approachesin hardware implement at ion can effectively and rapidly deploy complex neural models. We have thoroughly evaluated the Hodgkin-Huxl ey model , recognized as a comprehensive biological model comprising fournonli near differential equations with complex functions. Due to its complexity and implement at ion challenges, we have f ocused on developing a more straight forward model with optimal implement at ion capabilities. During the FPGA hardware implement at ion phase, we utilized the VHDL hardware description l anguage. To speed up implement at ion and enhance efficiency, simplified equation sand 2𝑥 modules were employed. We designed the structure of the seequations to include only basic arithmetic operations, logical shifts, and clear equations. This approach leads to the development of an optimized neural model that reduces hardware resource consumption and operates at high speed, making i t highly beneficial for various applications across different fields.

Optimized Implement at ion of the Hodgkin-Huxley Model on FPGA Using 𝟐𝟐 Modules and Taylor Series Expansion for Enhanced Speed and Efficiency Keywords:

Neuron Hodgki n-Huxl ey (HH) , Dynami c Hodgki n-Huxl ey , Fi el d-Programmabl e Gat e Array (FPGA) , Modul es 2𝑥