PROJECT TITLE :

Digital Multiplierless Realization of Two-CoupledBiological Hindmarsh–Rose Neuron Model - 2016

ABSTRACT:

The economical modeling, simulation, and implementation of biological neural networks are key objectives of the neuromorphic research field, resulting in potential applications, like helping the search for new solutions to cure brain diseases, improved performance of robots, and the elemental study of neural network behavior. This brief proposes a changed biological Hindmarsh-Rose (HR) neuron model that's a lot of fitted to economical implementation on digital platforms. Simulation results show that the model can reproduce the required behaviors of the neuron. The proposed model is investigated, in terms of digital implementation feasibility and value, targeting a coffee-cost hardware implementation. Hardware implementation on a field-programmable gate array shows that the modified model mimics the biological behavior of various types of neurons, with higher performance and considerably lower hardware overhead price compared with the first HR model.


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Neural Nets Field Programmable Gate Arrays Logic Design Field-Programmable Gate Array (FPGA) Hindmarsh-Rose (HR) Neuron Model Spiking Neural Network (SNN)
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