9 citations · 14 across the 15 of their papers we have counts for
10 papers · 1 filter
Neuromorphic circuit for temporal odor encoding in turbulent environments
Shavika Rastogi, Nik Dennler, Michael Schmuker +1
Natural odor environments present turbulent and dynamic conditions, causing chemical signals to fluctuate in space, time, and intensity. While many species have evolved highly adap…
Limitations in odour recognition and generalisation in a neuromorphic olfactory circuit
Nik Dennler, André van Schaik, Michael Schmuker
Neuromorphic computing is one of the few current approaches that have the potential to significantly reduce power consumption in Machine Learning and Artificial Intelligence. Imam…
RAMAN: A Re-configurable and Sparse tinyML Accelerator for Inference on Edge
Adithya Krishna, Srikanth Rohit Nudurupati, Chandana D G +4
Deep Neural Network (DNN) based inference at the edge is challenging as these compute and data-intensive algorithms need to be implemented at low cost and low power while meeting t…
A Trainable Neuromorphic Integrated Circuit that Exploits Device Mismatch
Chetan Singh Thakur, Runchun Wang, Tara Julia Hamilton +2
Random device mismatch that arises as a result of scaling of the CMOS (complementary metal-oxide semi-conductor) technology into the deep submicron regime degrades the accuracy of…
Turn Down that Noise: Synaptic Encoding of Afferent SNR in a Single Spiking Neuron
Saeed Afshar, Libin George, Jonathan Tapson +3
We have added a simplified neuromorphic model of Spike Time Dependent Plasticity (STDP) to the Synapto-dendritic Kernel Adapting Neuron (SKAN). The resulting neuron model is the fi…
Racing to Learn: Statistical Inference and Learning in a Single Spiking Neuron with Adaptive Kernels
Saeed Afshar, Libin George, Jonathan Tapson +2
This paper describes the Synapto-dendritic Kernel Adapting Neuron (SKAN), a simple spiking neuron model that performs statistical inference and unsupervised learning of spatiotempo…