2021 BRN Discussion, page-7894

Sounak Dey - new related research

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Flexible Energy-Efficient Implementation of Adaptive Spiking Encoder for Neuromorphic Processors

M Zamani, M Ronchini, HA Huynh, H Farkhani… - 2021 IEEE International …, 2021
Neuromorphic computing could pave the way to a new generation of smart sensors
that can process signals locally through Spiking Neural Networks (SNNs). For this
paradigm to take hold, it is necessary to have an analog-to-spike encoder adaptable


Learning from Event Cameras with Sparse Spiking Convolutional Neural Networks

L Cordone, B Miramond, S Ferrante - arXiv preprint arXiv:2104.12579, 2021
Convolutional neural networks (CNNs) are now the de facto solution for computer
vision problems thanks to their impressive results and ease of learning. These
networks are composed of layers of connected units called artificial neurons, loosely


Adaptive Input-to-Neuron Interlink Development in Training of Spike-Based Liquid State Machines

S Hwang, J Lee, J Kung - 2021 IEEE International Symposium on Circuits and …, 2021
In this paper, we present a novel approach in developing input-to-neuron interlinks to
achieve better accuracy in spike-based liquid state machines. An energy-efficient
Spiking Neural Network suffer from lower accuracy in image classification compared


A Hardware-friendly Neuromorphic Spiking Neural Network for Frequency Detection and Fine Texture Decoding

M Mastella, E Chicca - 2021 IEEE International Symposium on Circuits and …, 2021
Humans can distinguish fabrics by their textures, even when they are finer than the
density of tactile sensors. Evidence suggests that this ability is produced by the
nervous system using an active touch strategy. When the finger slides over a texture


Neuromorphic Autonomous Spiking Encoding

RA Alzahrani, AC Parker - 2021 IEEE International Symposium on Circuits and …, 2021
Understanding how biological neurons encode information through neural signaling
is crucial in building rich computational hardware neuromorphic systems. This paper
creates a neuromorphic neuron model capable of processing and performing


Event-driven Local Gain Control on a Spiking Cochlea Sensor

I Kiselev, SC Liu - 2021 IEEE International Symposium on Circuits and …, 2021
Including local automatic gain control (AGC) circuitry into a silicon cochlea design
can be challenging because of transistor mismatch and model complexity. To
address this, we present an alternative system-level algorithm that implements