Computing inspired by the brain’s functions has emerged as the next generation of artificial intelligence. The Nature Conference on Neuromorphic Computing brought together researchers from a wide range of disciplines to discuss the unique challenges and opportunities of this budding field. Various research topics were covered by experts, including biological interpretation, software algorithm development, nano-device fabrication, hardware system design, and real-time applications.
In this conference, I made a poster presentation entitled as FPGA implementation of spiking neural networks: a case study. I investigated the impact of different neuron models on the classification performance of a spiking neural network (SNN). A parallel SNN accelerator was implemented on FPGA.
