Pulse width modulation (PWM) signals using spiking neuronal networks

This paper proposes a digital construction of Pulse Width Modulation (PWM) signals based on the Izhikevich neuron model using a Field Programmable Gate Array (FPGA) platform. The signals are intended for use in diverse electronics applications such as robotics and power converters. A spiking pattern was used to generate the input data and produce the PWM signals. A comparator was used to compare between the spiking pattern data and DC level parameters. The results validate that the proposed hardware can reproduce PWM signals with duty cycles from 0% to 100%.