34 citations · 77 across the 13 of their papers we have counts for
14 papers · 1 filter
Making a Spiking Net Work: Robust brain-like unsupervised machine learning
Peter G. Stratton, Andrew Wabnitz, Chip Essam +2
The surge in interest in Artificial Intelligence (AI) over the past decade has been driven almost exclusively by advances in Artificial Neural Networks (ANNs). While ANNs set state…
A Stochastic Approach to STDP
Runchun Wang, Chetan Singh Thakur, Tara Julia Hamilton +2
We present a digital implementation of the Spike Timing Dependent Plasticity (STDP) learning rule. The proposed digital implementation consists of an exponential decay generator ar…
Investigation of event-based memory surfaces for high-speed tracking, unsupervised feature extraction and object recognition
Saeed Afshar, Gregory Cohen, Tara Julia Hamilton +2
In this paper we compare event-based decaying and time based-decaying memory surfaces for high-speed eventbased tracking, feature extraction, and object classification using an eve…
A Reconfigurable Mixed-signal Implementation of a Neuromorphic ADC
Ying Xu, Chetan Singh Thakur, Tara Julia Hamilton +3
We present a neuromorphic Analogue-to-Digital Converter (ADC), which uses integrate-and-fire (I&F) neurons as the encoders of the analogue signal, with modulated inhibitions to dec…
A compact aVLSI conductance-based silicon neuron
Runchun Wang, Chetan Singh Thakur, Tara Julia Hamilton +2
We present an analogue Very Large Scale Integration (aVLSI) implementation that uses first-order lowpass filters to implement a conductance-based silicon neuron for high-speed neur…
A neuromorphic hardware architecture using the Neural Engineering Framework for pattern recognition
Runchun Wang, Chetan Singh Thakur, Tara Julia Hamilton +2
We present a hardware architecture that uses the Neural Engineering Framework (NEF) to implement large-scale neural networks on Field Programmable Gate Arrays (FPGAs) for performin…