Explanipedia

Unsupervised sparse coding-based spiking neural network for real-time spike sorting Open

Alexis Melot, Sean U. N. Wood, Yannick Coffinier, Pierre Yger, Fabien Alibart · 2025

Spike sorting is a crucial step in decoding multichannel extracellular neural signals, enabling the identification of individual neuronal activity. A key challenge in brain–machine interfaces is achieving real-time, low-power spike sorting…

End-to-end neuromorphic speech enhancement with PDM microphones <sup>*</sup> Open

Sidi Yaya Arnaud Yarga, Sean U. N. Wood · 2025

Enhancing speech in noisy environments is essential for applications like automatic speech recognition, hearing aids, and real-time voice interfaces, but remains challenging on low-power, always-on edge devices. Conventional systems rely o…

Unsupervised Sparse Coding-based Spiking Neural Network for Real-time Spike Sorting Open

Alexis Melot, Sean U. N. Wood, Yannick Coffinier · 2025

Spike sorting is a crucial step in decoding multichannel extracellular neural signals, enabling the identification of individual neuronal activity. A key challenge in brain-machine interfaces (BMIs) is achieving real-time, low-power spike …

Accelerating spiking neural networks with parallelizable leaky integrate-and-fire neurons<sup>*</sup> Open

Sidi Yaya Arnaud Yarga, Sean U. N. Wood · 2025

Spiking neural networks (SNNs) express higher biological plausibility and excel at learning spatiotemporal features while consuming less energy than conventional artificial neural networks, particularly on neuromorphic hardware. The leaky …

Neuromorphic Keyword Spotting with Pulse Density Modulation MEMS Microphones Open

Sidi Yaya Arnaud Yarga, Sean U. N. Wood · 2024

The Keyword Spotting (KWS) task involves continuous audio stream monitoring to detect predefined words, requiring low energy devices for continuous processing. Neuromorphic devices effectively address this energy challenge. However, the ge…

Accelerating Spiking Neural Networks with Parallelizable Leaky Integrate-and-Fire Neurons Open

Sidi Yaya Arnaud Yarga, Sean U. N. Wood · 2024

Spiking Neural Networks (SNNs) express higher biological plausibility and excel at learning spatiotemporal features while consuming less energy than conventional Artificial Neural Networks (ANNs), particularly on neuromorphic hardware. The…

Do try this at home: Age prediction from sleep and meditation with large-scale low-cost mobile EEG Open

Hubert Banville, Maurice Abou Jaoude, Sean U. N. Wood, Chris Aimone, Sebastian C. Holst , et al. · 2024

Electroencephalography (EEG) is an established method for quantifying large-scale neuronal dynamics which enables diverse real-world biomedical applications, including brain-computer interfaces, epilepsy monitoring, and sleep staging. Adva…

Accelerating SNN Training with Stochastic Parallelizable Spiking Neurons Open

Sidi Yaya Arnaud Yarga, Sean U. N. Wood · 2023

Spiking neural networks (SNN) are able to learn spatiotemporal features while using less energy, especially on neuromorphic hardware. The most widely used spiking neuron in deep learning is the Leaky Integrate and Fire (LIF) neuron. LIF ne…

Hardware-aware Training Techniques for Improving Robustness of Ex-Situ Neural Network Transfer onto Passive TiO2 ReRAM Crossbars Open

Philippe Drolet, Raphaël Dawant, Victor Yon, Pierre-Antoine Mouny, Matthieu Valdenaire , et al. · 2023

Passive resistive random access memory (ReRAM) crossbar arrays, a promising emerging technology used for analog matrix-vector multiplications, are far superior to their active (1T1R) counterparts in terms of the integration density. Howeve…

Do try this at home: Age prediction from sleep and meditation with large-scale low-cost mobile EEG Open

Hubert Banville, Maurice Abou Jaoude, Sean U. N. Wood, Chris Aimone, Sebastian C. Holst , et al. · 2023

EEG is an established method for quantifying large-scale neuronal dynamics which enables diverse real-world biomedical applications including brain-computer interfaces, epilepsy monitoring and sleep staging. Advances in sensor technology h…

Efficient Spike Encoding Algorithms for Neuromorphic Speech Recognition Open

Sidi Yaya Arnaud Yarga, Jean Rouat, Sean U. N. Wood · 2022

Spiking Neural Networks (SNN) are known to be very effective for neuromorphic processor implementations, achieving orders of magnitude improvements in energy efficiency and computational latency over traditional deep learning approaches. C…

Robust learning from corrupted EEG with dynamic spatial filtering Open

Hubert Banville, Sean U. N. Wood, Chris Aimone, Denis A. Engemann, Alexandre Gramfort · 2022

Robust learning from corrupted EEG with dynamic spatial filtering Open

Hubert Banville, Sean U. N. Wood, Chris Aimone, Denis A. Engemann, Alexandre Gramfort · 2021

Building machine learning models using EEG recorded outside of the laboratory setting requires methods robust to noisy data and randomly missing channels. This need is particularly great when working with sparse EEG montages (1-6 channels)…

Evaluation of a Vision-to-Audition Substitution System that Provides 2D WHERE Information and Fast User Learning Open

Louis Commère, Sean U. N. Wood, Jean Rouat · 2020

Vision to audition substitution devices are designed to convey visual information through auditory input. The acceptance of such systems depends heavily on their ease of use, training time, reliability and on the amount of coverage of onli…

Unsupervised Low Latency Speech Enhancement With RT-GCC-NMF Open

Sean U. N. Wood, Jean Rouat · 2019

In this paper, we present RT-GCC-NMF: a real-time (RT), two-channel blind speech enhancement algorithm that combines the non-negative matrix factorization (NMF) dictionary learning algorithm with the generalized cross-correlation (GCC) spa…

A Flexible Bio-Inspired Hierarchical Model for Analyzing Musical Timbre Open

Mohammad Adeli, Jean Rouat, Sean U. N. Wood, Stéphane Molotchnikoff, Éric Plourde · 2016

A flexible and multipurpose bio-inspired hierarchical model for analyzing musical timbre is presented in this paper. Inspired by findings in the fields of neuroscience, computational neuroscience, and psychoacoustics, not only does the mod…

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