7 citations · 14 across the 8 of their papers we have counts for
8 papers
Learning to See via Epiretinal Implant Stimulation in silico with Model-Based Deep Reinforcement Learning
Jacob Lavoie, Marwan Besrour, William Lemaire +3
Objective: Diseases such as age-related macular degeneration and retinitis pigmentosa cause the degradation of the photoreceptor layer. One approach to restore vision is to electri…
Adaptive Central Frequencies Locally Competitive Algorithm for Speech
Soufiyan Bahadi, Eric Plourde, Jean Rouat
Neuromorphic computing, inspired by nervous systems, revolutionizes information processing with its focus on efficiency and low power consumption. Using sparse coding, this paradig…
Maximizing Information in Neuron Populations for Neuromorphic Spike Encoding
Ahmad El Ferdaoussi, Eric Plourde, Jean Rouat
Neuromorphic applications emulate the processing performed by the brain by using spikes as inputs instead of time-varying analog stimuli. Therefore, these time-varying stimuli have…
Efficient Sparse Coding with the Adaptive Locally Competitive Algorithm for Speech Classification
Soufiyan Bahadi, Eric Plourde, Jean Rouat
Researchers are exploring novel computational paradigms such as sparse coding and neuromorphic computing to bridge the efficiency gap between the human brain and conventional compu…
Single Channel Speech Enhancement Using U-Net Spiking Neural Networks
Abir Riahi, Éric Plourde
Speech enhancement (SE) is crucial for reliable communication devices or robust speech recognition systems. Although conventional artificial neural networks (ANN) have demonstrated…
Evaluation of Neuromorphic Spike Encoding of Sound Using Information Theory
Ahmad El Ferdaoussi, Éric Plourde, Jean Rouat
The problem of spike encoding of sound consists in transforming a sound waveform into spikes. It is of interest in many domains, including the development of audio-based spiking ne…
Adaptive Approach For Sparse Representations Using The Locally Competitive Algorithm For Audio
Soufiyan Bahadi, Jean Rouat, Éric Plourde
Gammachirp filterbank has been used to approximate the cochlea in sparse coding algorithms. An oriented grid search optimization was applied to adapt the gammachirp's parameters an…
Classification of auditory stimuli from EEG signals with a regulated recurrent neural network reservoir
Marc-Antoine Moinnereau, Thomas Brienne, Simon Brodeur +3
The use of electroencephalogram (EEG) as the main input signal in brain-machine interfaces has been widely proposed due to the non-invasive nature of the EEG. Here we are specifica…