PROJECT TITLE :
Guest Editorial on Health-Care Management and Optimization
The economical modeling, simulation, and implementation of biological neural networks are key objectives of the neuromorphic analysis field, resulting in potential applications, like aiding the search for brand spanking new solutions to cure brain diseases, improved performance of robots, and the basic 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 will reproduce the required behaviors of the neuron. The proposed model is investigated, in terms of digital implementation feasibility and price, targeting an occasional-value hardware implementation. Hardware implementation on a field-programmable gate array shows that the modified model mimics the biological behavior of different sorts of neurons, with higher performance and significantly lower hardware overhead value compared with the initial HR model.
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