4 citations · 4 across the 5 of their papers we have counts for
5 papers
A Neuromodulable Current-Mode Silicon Neuron for Robust and Adaptive Neuromorphic Systems
Loris Mendolia, Chenxi Wen, Elisabetta Chicca +4
Neuromorphic engineering makes use of mixed-signal analog and digital circuits to directly emulate the computational principles of biological brains. Such electronic systems offer…
Scaling Effects of Transistor Leakage Current and IR Drop on 1T1R Memory Arrays
Junren Chen, Giacomo Indiveri
1T1R (1-transistor-1-resistor) memory crossbar arrays represent a promising solution for compute-in-memory matrix-vector multiplication accelerators and embedded or storage-class m…
TEXEL: A neuromorphic processor with on-chip learning for beyond-CMOS device integration
Hugh Greatorex, Ole Richter, Michele Mastella +10
Recent advances in memory technologies, devices and materials have shown great potential for integration into neuromorphic electronic systems. However, a significant gap remains be…
Accurate Mapping of RNNs on Neuromorphic Hardware with Adaptive Spiking Neurons
Gauthier Boeshertz, Giacomo Indiveri, Manu Nair +1
Thanks to their parallel and sparse activity features, recurrent neural networks (RNNs) are well-suited for hardware implementation in low-power neuromorphic hardware. However, map…
Distributed Representations Enable Robust Multi-Timescale Symbolic Computation in Neuromorphic Hardware
Madison Cotteret, Hugh Greatorex, Alpha Renner +6
Programming recurrent spiking neural networks (RSNNs) to robustly perform multi-timescale computation remains a difficult challenge. To address this, we describe a single-shot weig…