Spiking Neural Networks -- Part I: Detecting Spatial Patterns

Understand

Spiking Neural Networks (SNNs) are biologically inspired machine learning models that build on dynamic neuronal models processing binary and sparse spiking signals in an event-driven, online, fashion.

• SNNs can be implemented on neuromorphic computing platforms that are emerging as energy-efficient co-processors for learning and inference.
• This is the first of a series of three papers that introduce SNNs to an audience of engineers by focusing on models, algorithms, and applications.
• In this first paper, we first cover neural models used for conventional Artificial Neural Networks (ANNs) and SNNs.