25 citations · 29 across the 7 of their papers we have counts for
4 papers · 1 filter
Zephyr: An Efficient Audio Denoising System Using Spiking Neural Networks Enabled With A Sparsity-Aware Flexible FPGA PE Array
Cheng-En Chang, Chi-Wei Kao, Chung-Lun Yang +4
In this work we look to neuromorphic computing to solve the power consumption problem that audio denoising neural networks face on edge devices like smartphones, wireless headphone…
Learning to Focus Synthetic Aperture Radar On-line with State-Space Models
Sebastian Fieldhouse, Roberto Del Prete, Gabriele Daga +3
Conventional focusing methods for Synthetic Aperture Radar (SAR) employ block processing efficiently but remain latency-heavy processes that prevent the realisation of a closed-loo…
Silicon Aware Neural Networks
Sebastian Fieldhouse, Kea-Tiong Tang
Recent work in the machine learning literature has demonstrated that deep learning can train neural networks made of discrete logic gate functions to perform simple image classific…
A 0.5-V Linear Neuromorphic Voltage-to-Spike Encoder Using a Bulk-Driven Transconductor
Meysam Akbari, Erika Covi, Kea-Tiong Tang
This work introduces an ultralow-power voltage-to-spike encoder that achieves near-linear voltage-to-firing-rate conversion by pairing a linearized bulk-driven transconductor with…