89 citations · 445 across the 19 of their papers we have counts for
6 papers · 1 filter
Low-Power Low-Latency Keyword Spotting and Adaptive Control with a SpiNNaker 2 Prototype and Comparison with Loihi
Yexin Yan, Terrence C. Stewart, Xuan Choo +7
We implemented two neural network based benchmark tasks on a prototype chip of the second-generation SpiNNaker (SpiNNaker 2) neuromorphic system: keyword spotting and adaptive robo…
Spiking Associative Memory for Spatio-Temporal Patterns
Simon Davidson, Stephen B. Furber, Oliver Rhodes
Spike Timing Dependent Plasticity is form of learning that has been demonstrated in real cortical tissue, but attempts to use it for artificial systems have not produced good resul…
Dynamic Power Management for Neuromorphic Many-Core Systems
Sebastian Hoeppner, Bernhard Vogginger, Yexin Yan +12
This work presents a dynamic power management architecture for neuromorphic many core systems such as SpiNNaker. A fast dynamic voltage and frequency scaling (DVFS) technique is pr…
Efficient Reward-Based Structural Plasticity on a SpiNNaker 2 Prototype
Yexin Yan, David Kappel, Felix Neumaerker +7
Advances in neuroscience uncover the mechanisms employed by the brain to efficiently solve complex learning tasks with very limited resources. However, the efficiency is often lost…
Noisy Softplus: an activation function that enables SNNs to be trained as ANNs
Qian Liu, Yunhua Chen, Steve Furber
We extended the work of proposed activation function, Noisy Softplus, to fit into training of layered up spiking neural networks (SNNs). Thus, any ANN employing Noisy Softplus neur…
An associative memory for the on-line recognition and prediction of temporal sequences
J. Bose, S. B. Furber, J. L. Shapiro
This paper presents the design of an associative memory with feedback that is capable of on-line temporal sequence learning. A framework for on-line sequence learning has been prop…