Neurons are the basic blocks in the Central Nervous
System (CNS). Simulation and hardware realization of these
blocks are vital in neuromorphic engineering. This paper presents
a set of multiplierless mathematical equations based on 2
terms to achieve a low-cost, high-speed, and high-accuracy digital
implementation of Hodgkin-Huxley (HH) neuron model. The
HH model is the most complicated and high-accuracy among
the mathematical neuron models. The proposed model can
reproduce spiking behaviors of the original HH model with
high precision. To validate the mathematical simulation results,
the proposed model has been synthesized and implemented on
Field-Programmable Gate Array (FPGA) development board.
Hardware synthesis and physical implementations reveal that
the biological behavior of different spiking patterns can be
reproduced with higher performance and significantly lower
implementation costs compared with the original HH model.
Also, in this approach the maximum frequency of 200 MHz is
achievable which is valuable in comparison with other similar
works.