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Bertrand Rivet

7 accepted papers

2020

Gradient-Based Algorithm with Spatial Regularization for Optimal Sensor Placement

ICASSP 2020accepted

In this paper, we are interested in optimal sensor placement for signal extraction. Recently, a new criterion based on output signal to noise ratio has been proposed for sensor placement. However, to solve the optimization problem, a greedy approach is used over a grid, which is not optimal. To impr…

Cited by 0SourceScholar
2019

Heart Rate Estimation from Phonocardiogram Signals Using Non-negative Matrix Factorization

ICASSP 2019accepted

Electrocardiogram (ECG) is classically considered for heart rate (HR) estimation. However in certain conditions, its use may be difficult and alternative techniques, such as phonocardiograhpy (PCG), are investigated. For PCG signals, in most studies, the challenge is to detect and annotate the heart…

Cited by 0SourceScholar
2019

Optimal Sensor Placement for Signal Extraction

ICASSP 2019accepted

This paper focuses on the optimal sensor placement problem with the purpose of signal extraction in an underdetermined noisy setting. Assuming prior information on the spatial gain of the measured signal and on the spatial noise correlation, we propose a sensor placement criterion based on the maxim…

Cited by 0SourceScholar
2017

Blind compensation of polynomial mixtures of Gaussian signals with application in nonlinear blind source separation

ICASSP 2017accepted

In this paper, a proof is provided to show that Gaussian signals will lose their Gaussianity if they are passed through a polynomial of an order greater than 1. This can help in blind compensation of polynomial nonlinearities on Gaussian sources by forcing the output to follow a Gaussian distributio…

Cited by 0SourceScholar
2015

A multi-modal approach using a non-parametric model to extract fetal ECG

ICASSP 2015accepted

This study presents a non-parametric method to extract and separate maternal and fetal electrocardiogram (ECG) from an abdominal channel. The proposed method relies on the use of two additional reference signals related to the maternal and to the fetal ECGs. The fetal and maternal ECG contributions…

Cited by 0SourceScholar
2015

Real-time independent vector analysis with Student's t source prior for convolutive speech mixtures

ICASSP 2015accepted

A common approach to blind source separation is to use independent component analysis. However when dealing with realistic convolutive audio and speech mixtures, processing in the frequency domain at each frequency bin is required. As a result this introduces the permutation problem, inherent in ind…

Cited by 0SourceScholar