Hardware design of spiking neural networks for energy-efficient brain inspired computing

Artificial neural networks are experiencing an exclusive interest due to the unprecedented computing power capabilities the computers reached and the explosion of open data. The recent results of deep neural networks on image classification has given neural networks the leading role in machine learning algorithms and artificial intelligence research. However, these systems are energy hungry which makes them not suitable for embedded systems.Thus,dedicated hardware accelerators fitting the parallel and distributed computation paradigm have to be implemented.