Publications associées à Signal separation

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

Ketson Roberto Maximiano Dos Santos

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

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

Crystal Orientation Drives the Interface Physics at Two/Three-Dimensional Hybrid Perovskites

Jacques-Edouard Moser, Mohammad Khaja Nazeeruddin, Sanghyun Paek, Giulia Grancini, Kyung Taek Cho, Cristina Roldán Carmona, Valentin Ianis Emmanuel Queloz, Marine Eva Fedora Bouduban

Combining halide perovskites with tailored dimensionality into two/three-dimensional (2D/3D) systems has revealed a powerful strategy to boost the performances of perovskite photovoltaics (PVs). Despite recent advances, a clear understanding of the intimat ...

2019

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

Joint Anomaly Detection and Spectral Unmixing for Planetary Hyperspectral Images

Harold Gabriel Eugène Justin Clenet, Nicolas Courty

Hyperspectral (HS) images are commonly used in the context of planetary exploration, particularly for the analysis of the composition of planets. As several instruments have been sent throughout the Solar System, a huge quantity of data is getting availabl ...

Institute of Electrical and Electronics Engineers2016

Binary Sparse Coding of Convolutive Mixtures for Sound Localization and Separation via Spatialization

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei, Mohammadjavad Taghizadeh, Saeid Haghighatshoar

We propose a sparse coding approach to address the problem of source-sensor localization and speech reconstruction. This approach relies on designing a dictionary of spatialized signals by projecting the microphone array recordings into the array manifolds ...

Institute of Electrical and Electronics Engineers2016

Iterative signal separation based multiple phase estimation in digital holographic interferometry

Pramod Rastogi, Rishikesh Dilip Kulkarni

We propose a new method for signal separation from a multicomponent interference field recorded in a digital holographic interferometry setup. The setup consisting of multiple object illuminating beams results in an interference field containing multiple s ...

Optical Society of America2015

Signal structure: from manifolds to molecules and structured sparsity

Sofia Karygianni

Effective representation methods and proper signal priors are crucial in most signal processing applications. In this thesis we focus on different structured models and we design appropriate schemes that allow the discovery of low dimensional latent struct ...

EPFL2015

Multiple phase estimation via signal separation using a windowed Fourier transform in digital holographic interferometry

Pramod Rastogi, Rishikesh Dilip Kulkarni

This paper proposes a novel method for the simultaneous estimation of multiple interference phases from a single recording of the interference field in a multi-wave digital holographic interferometry set-up. The method involves the separation of signal com ...

Institute of Physics2015

Reverberant Audio Source Separation via Sparse and Low-Rank Modeling

Pierre Vandergheynst

The performance of audio source separation from underde- termined convolutive mixture assuming known mixing filters can be significantly improved by using an analysis sparse prior optimized by a reweighting l1 scheme and a wideband data- fidelity term, as ...

IEEE Institute of Electrical and Electronics Engineers2014

Model-based Sparse Component Analysis for Reverberant Speech Localization

Hervé Bourlard, Volkan Cevher, Afsaneh Asaei, Mohammadjavad Taghizadeh

In this paper, the problem of multiple speaker localization via speech separation based on model-based sparse recovery is studies. We compare and contrast computational sparse optimization methods incorporating harmonicity and block structures as well as a ...

2014

Simultaneous measurement of in-plane and out-of-plane displacements using pseudo-Wigner-Hough transform

Pramod Rastogi, Rishikesh Dilip Kulkarni

A new method based on pseudo-Wigner-Hough transform is proposed for the simultaneous measurement of the in-plane and out-of-plane displacements using digital holographic moire. Multiple interference phases corresponding to the in-plane and out-of-plane dis ...

Optical Society of America2014

Disentangling Dynamic Networks: Separated and Joint Expressions of Functional Connectivity Patterns in Time

Dimitri Nestor Alice Van De Ville, Nora Leonardi

Resting-state functional connectivity (FC) is highly variable across the duration of a scan. Groups of coevolving connections, or reproducible patterns of dynamic FC (dFC), have been revealed in fluctuating FC by applying unsupervised learning techniques. ...

Wiley-Blackwell2014

Planck 2013 results. IX. HFI spectral response

Julien Lesgourgues, Xin Chen, Fabio Finelli

The Planck High Frequency Instrument (HFI) spectral response was determined through a series of ground based tests conducted with the HFI focal plane in a cryogenic environment prior to launch. The main goal of the spectral transmission tests was to measur ...

Edp Sciences S A2014

Planck 2013 results. XIII. Galactic CO emission

Julien Lesgourgues, Xin Chen, Fabio Finelli

Rotational transition lines of CO play a major role in molecular radio astronomy as a mass tracer and in particular in the study of star formation and Galactic structure. Although a wealth of data exists for the Galactic plane and some well-known molecular ...

Edp Sciences S A2014

Sparse Reverberant Audio Source Separation via Reweighted Analysis

Jean-Philippe Thiran, Pierre Vandergheynst, Yves Wiaux, Rafael Eduardo Carrillo Rangel

We propose a novel algorithm for source signals estimation from an underdetermined convolutive mixture assuming known mixing filters. Most of the state-of-the-art methods are dealing with anechoic or short reverberant mixture, assuming a synthesis sparse p ...

Institute of Electrical and Electronics Engineers2013