Sound-recognition using Spiking Neural Networks

The development of the Spiking Neural Network (SNN) offers great potential in combination with new types of event-based sensors, by exploiting the embedded temporal information. When combined with dedicated neuromorphic hardware it enables ultra-low power solutions and local on-chip learning. This work implements and presents a viable...

Design Space Exploration of a Neuromorphic ECG Classification System using a Spiking Self-Organizing Map

The Self-Organizing Map (SOM) is an unsupervised neural networktopology that incorporates competitive learning for the classicationof data. In this thesis we investigate the design space of a system incorporating such a topology based on Spiking Neural Networks (SNNs), and apply it to classifying electrocardiogram (ECG) beats. We present novel...