Evaluation, improvement and implementation of an artificial neuron on FPGA

In this paper, simulation the behavior of a single neuron, and the implementation of the hardware of a biochemical neuron according to the Hodgkin-Huxley model is investigated, that is closely resembles the real neuron, and its implementation is very difficult, But with the help of re-configuration and implementation on parallel, the FPGAbased hardware design of the optimized neuronal system was performed. For this purpose, we have been using a variety of hardware ideas for the implementation of single-neurons to design the best type of complete neuron based on high speed, compactness, high precision and expandability. Some of the ideas in design and implementation include doing limited digital calculations, simplifying mathematical functions, and converting floating-point operations to fixed-point, which have the optimization and reduction of consumable hardware, have the maximum parallelism and the precision of the production of the output signals. The model presented in this paper is very important for many scientists in the field of cognitive neuroscience.