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This paper describes a model and an implementation of spiking neurons for embedded microcontrollers with few bytes of memory and very low power consumption. The proposed model consists of an elementary neuron network that used Hebbian Learning to train a robot to respond to the environment implementing Artificial Intelligence (AI) in robot. The model is implemented using ATMEGA8 Microcontroller based on AVR RISC Architecture and tested with an ability to move forward and Backward according to intensity of light without human intervention and external computers.
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