Concept

Signal separation

Publications associées (64)

Motor-Unit Ordering of Blindly-Separated Surface-EMG Signals for Gesture Recognition

Hand gestures are one of the most natural and expressive way for humans to convey information, and thus hand gesture recognition has become a research hotspot in the human-machine interface (HMI) field. In particular, biological signals such as surface ele ...

SPRINGER INTERNATIONAL PUBLISHING AG2023

Manifold Learning-Based Polynomial Chaos Expansions For High-Dimensional Surrogate Models

In this work we introduce a manifold learning-based method for uncertainty quantification (UQ) in systems describing complex spatiotemporal processes. Our first objective is to identify the embedding of a set of high-dimensional data representing quantitie ...

2022

The Spiked Matrix Model With Generative Priors

Florent Gérard Krzakala, Lenka Zdeborová, Bruno Loureiro, Bruno Loureiro

We investigate the statistical and algorithmic properties of random neural-network generative priors in a simple inference problem: spiked-matrix estimation. We establish a rigorous expression for the performance of the Bayes-optimal estimator in the high- ...

2020

Nested oscillations and brain connectivity during sequential stages of feature-based attention

David Pascucci, Gijs Plomp

Brain mechanisms of visual selective attention involve both local and network-level activity changes at specific oscillatory rhythms, but their interplay remains poorly explored. Here, we investigate anticipatory and reactive effects of feature-based atten ...

2020

A visual working memory dataset collection with bootstrap Independent Component Analysis for comparison of electroencephalographic preprocessing pipelines

Fiorenzo Artoni

Here we present an electroencephalographic (EEG) collection of 71-channel datasets recorded from 14 subjects (7 males, 7 females, aged 20–40 years) while performing a visual working memory task with a T set of 150 Independent Component Analysis (ICA) decom ...

2019

Learning Feature Maps of the Koopman Operator: A Subspace Viewpoint

Colin Neil Jones, Yingzhao Lian

The Koopman operator was recently shown to be a useful method for nonlinear system identification and controller design. However, the scalability of current data-driven approaches is limited by the selection of feature maps. In this paper, we present a new ...

IEEE2019

Workshops of the seventh international brain-computer interface meeting: not getting lost in translation

Kyuhwa Lee, Ricardo Andres Chavarriaga Lozano, Anton Nijholt

The Seventh International Brain-Computer Interface (BCI) Meeting was held May 21-25th, 2018 at the Asilomar Conference Grounds, Pacific Grove, California, United States. The interactive nature of this conference was embodied by 25 workshops covering topics ...

TAYLOR & FRANCIS LTD2019

Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition

Fiorenzo Artoni

Independent Component Analysis (ICA) has proven to be an effective data driven method for analyzing EEG data, separating signals from temporally and functionally independent brain and non-brain source processes and thereby increasing their definition. Dime ...

2018

"Do you feel in control?": Towards Novel Approaches to Characterise, Manipulate and Measure the Sense of Agency in Virtual Environments

Louis Philippe Albert, Camille Marie Jeunet

While the Sense of Agency (SoA) has so far been predominantly characterised in VR as a component of the Sense of Embodiment, other communities (e.g., in psychology or neurosciences) have investigated the SoA from a different perspective proposing complemen ...

2018

Signal Analysis Based on Complex Wavelet Signs

Martin Kurt Storath

We propose a signal analysis tool based on the sign (or the phase) of complex wavelet coefficients, which we call a signature. The signature is defined as the fine-scale limit of the signs of a signal's complex wavelet coefficients. We show that the signat ...

Elsevier2017

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